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Kernel Extreme Learning Machine: An Efficient Model for Estimating Daily Dew Point Temperature Using Weather Data

Meysam Alizamir, Sungwon Kim, Mohammad Zounemat-Kermani, Salim Heddam, Nam Won Kim, Vijay P. Singh
<span title="">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cdphbut2xvdpze2ou6uov4erve" style="color: black;">Water</a> </i> &nbsp;
(RHMIN), vapor pressure (VP), soil temperature (ST), solar radiation (SR), and dew point temperature (Tdew) were utilized to investigate the applied predictive models.  ...  Accurate estimation of dew point temperature (Tdew) has a crucial role in sustainable water resource management.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/w12092600">doi:10.3390/w12092600</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/84016fdf0c02481599c346bec63e33c0">doaj:84016fdf0c02481599c346bec63e33c0</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wup2yhifzjhgbe4mxhon34ilwe">fatcat:wup2yhifzjhgbe4mxhon34ilwe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201103163347/https://res.mdpi.com/d_attachment/water/water-12-02600/article_deploy/water-12-02600-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8f/27/8f278b5722274c585297074ec590fb68ae653976.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/w12092600"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence

Aleksandra Wlodarczyk, Patrycja Molek, Bogdan Bochenek, Agnieszka Wypych, Jadwiga Nessler, Jaroslaw Zalewski
<span title="2022-04-08">2022</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dyhiozglrzgszfrxloytlygd7u" style="color: black;">Frontiers in Cardiovascular Medicine</a> </i> &nbsp;
The predicted daily number of ACS has been estimated with the Random Forest machine learning system based on air temperature (°C), air pressure (hPa), dew point temperature (Td) (°C), relative humidity  ...  The correlation between the predicted and observed daily number of ACS derived from machine learning was 0.82 with 95% CI of 0.80–0.84 (P &lt; 0.001).  ...  Of all the weather parameters, the highest variable importance for machine learning (range 0-1) involved dew point temperature daily range, air pressure daily range and its maximum, and RH maximum with  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fcvm.2022.830823">doi:10.3389/fcvm.2022.830823</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35463797">pmid:35463797</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC9024050/">pmcid:PMC9024050</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nbntu7etffgcfo2rkasf37lds4">fatcat:nbntu7etffgcfo2rkasf37lds4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220606223513/https://fjfsdata01prod.blob.core.windows.net/articles/files/830823/pubmed-zip/.versions/1/.package-entries/fcvm-09-830823/fcvm-09-830823.pdf?sv=2018-03-28&amp;sr=b&amp;sig=dTpLeQlvjpTmkPxyr%2FLkWZ%2FouA7ThMQpOFA36amdr1c%3D&amp;se=2022-06-06T22%3A35%3A42Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fcvm-09-830823.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/85/76/85768470c17e5830b46004e319f2c1a22cd63cab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fcvm.2022.830823"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024050" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Dew Point Time Series Forecasting at the North Dakota

Bugrayhan Bickici Arikan, Luo Jiechen, Ibrahim I D Sabbah, Ahmed Ewees, Rajab Homsi, Sadeq Oleiwi Sulaiman
<span title="2021-08-31">2021</span> <i title="Knowledge-based Engineering and Sciences"> Knowledge-Based Engineering and Sciences </i> &nbsp;
Dew point temperature (Tdew) is one of the complex hydrological processes that highly essential to be quantified accurately for several catchment activities such as crops, agriculture, and others.  ...  In this study, three types of models' recursive strategy, direct strategy, and DirRec which is the combination of recursive and direct strategies were adopted to obtain h-steps ahead predictions of Tdew  ...  Also, recently there have been several investigation on the implementation on advance machine learning approaches for the average dew point temperature prediction [29] , [30] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.51526/kbes.2021.2.2.24-34">doi:10.51526/kbes.2021.2.2.24-34</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qk3vjb57hbhulebbupsdrol6pe">fatcat:qk3vjb57hbhulebbupsdrol6pe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210901035413/https://kbes.journals.publicknowledgeproject.org/index.php/kbes/article/download/5715/4745" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/78/76/78760e13916c72749cacc98a61e1c55c7de35c1c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.51526/kbes.2021.2.2.24-34"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Dew Point Temperature Estimation: Application of Artificial Intelligence Model Integrated with Nature-Inspired Optimization Algorithms

Sujay Naganna, Paresh Deka, Mohammad Ghorbani, Seyed Biazar, Nadhir Al-Ansari, Zaher Yaseen
<span title="2019-04-10">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cdphbut2xvdpze2ou6uov4erve" style="color: black;">Water</a> </i> &nbsp;
Daily time scale measured weather information, such as wet bulb temperature (WBT), vapor pressure (VP), relative humidity (RH), and dew point temperature, was used to build the proposed predictive models  ...  Dew point temperature (DPT) is known to fluctuate in space and time regardless of the climatic zone considered.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/w11040742">doi:10.3390/w11040742</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/js4t4fvlqnfm7f736nqhabwt3u">fatcat:js4t4fvlqnfm7f736nqhabwt3u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502071445/https://res.mdpi.com/water/water-11-00742/article_deploy/water-11-00742-v2.pdf?filename=&amp;attachment=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a8/55/a855598ba85c988b41be95aab20ecaf78d77a314.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/w11040742"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Spatial-Temporal Approach for Predicting Rainfall in Tropical Country

Indrabayu, Surya Aditama, A. Ais Prayogi, Saleh Pallu, Andani Achmad, Intan Sari Areni
<span title="">2019</span> <i title="ICIC International"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdc7itdnm5ekhoql3paw7mmr4q" style="color: black;">ICIC Express Letters</a> </i> &nbsp;
This research predicts rainfall in Makassar based on temperature, humidity, visibility, and dew point in Ambon and Palembang using extreme learning machine.  ...  This spatial region is selected based on correlation of temperature and rainfall between Makassar with Ambon and Palembang.  ...  is using five from eight available types of metrological data based on their level of correlation that is rainfall, temperature, humidity, dew points, and visibility.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24507/icicel.13.02.113">doi:10.24507/icicel.13.02.113</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/43zkr5tsufh5jpg7r453igmpum">fatcat:43zkr5tsufh5jpg7r453igmpum</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220308110556/http://www.icicel.org/ell/contents/2019/2/el-13-02-04.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ca/68/ca6873b9623806f785d6fbba2b3b68f68ae771f7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24507/icicel.13.02.113"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Modeling Hourly Soil Temperature Using Deep BiLSTM Neural Network

Cong Li, Yaonan Zhang, Xupeng Ren
<span title="2020-07-17">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/63zsvf7vxzfznojpqgfvpyk2lu" style="color: black;">Algorithms</a> </i> &nbsp;
Although numerous machine learning models have been used in the prediction of ST, and good results have been obtained, most of the current studies have focused on daily or monthly ST predictions, while  ...  The method considers the hourly ST prediction to be the superposition of two parts, namely, the daily average ST prediction and the ST amplitude (the difference between the hourly ST and the daily average  ...  The results show that the four methods can provide ideal ST prediction at all depths, and the extreme learning machine (ELM) performs best.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/a13070173">doi:10.3390/a13070173</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gtrvxvebpfcf5esihdroraxv5e">fatcat:gtrvxvebpfcf5esihdroraxv5e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201106220228/https://res.mdpi.com/d_attachment/algorithms/algorithms-13-00173/article_deploy/algorithms-13-00173.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/30/89/30893590aa1756cdcecf1e9d18eb408d893ac808.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/a13070173"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

Aleksandra Bączkiewicz, Jarosław Wątróbski, Wojciech Sałabun, Joanna Kołodziejczyk
<span title="2021-05-22">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the  ...  The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators  ...  Currently, models based on machine learning using Artificial Neural Networks and based on historical data are being tested.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app11114757">doi:10.3390/app11114757</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mczekbzw55ar5hcumw3yeuxmpy">fatcat:mczekbzw55ar5hcumw3yeuxmpy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210528132449/https://res.mdpi.com/d_attachment/applsci/applsci-11-04757/article_deploy/applsci-11-04757-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/63/a0/63a06071ebf4931ad2d03c6daf5ef2b3bf841598.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app11114757"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Evaluation of models for the dew point temperature determination

Krzysztof Górnicki, Radosław Winiczenko, Agnieszka Kaleta, Aneta Choińska
<span title="2017-05-04">2017</span> <i title="Uniwersytet Warminsko-Mazurski"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/e467i5q7mfb6tas5ptmd7xxpqu" style="color: black;">Technical Sciences</a> </i> &nbsp;
The accuracy of the available from the literature models for the dew point temperature determination was compared. The proposal of the modelling using artificial neural networks was also given.  ...  Proposed ANN model gave the good results in determining the dew point temperature (MBE=-0.0038 K, RMSE=0.1373 K, R=0.9999, χ2=0.0189 K2).  ...  AMIRMOJAHEDI et al. (2016) used method by hybridizing the extreme learning machine (ELM) with wavelet transform (WT) algorithm to predict daily dew point temperature.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31648/ts.5425">doi:10.31648/ts.5425</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6n57pg3u5vhz7ls7okgziqk5ti">fatcat:6n57pg3u5vhz7ls7okgziqk5ti</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200506220757/https://czasopisma.uwm.edu.pl/index.php/ts/article/download/5425/4127" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0c/e1/0ce198c35327c936ff3fc16b561b27a65e80bf99.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31648/ts.5425"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Predicting Urban Reservoir Levels Using Statistical Learning Techniques

Renee Obringer, Roshanak Nateghi
<span title="2018-03-26">2018</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
This study tested the abilities of eight statistical learning techniques to predict reservoir levels, given the current hydroclimatic conditions, and provide inferences on the key predictors of reservoir  ...  The results showed that random forest, an ensemble, tree-based method, was the best algorithm for predicting reservoir levels.  ...  In this study, the mean daily dew point temperature was used as a predictor. As shown in Fig. 3b , as the dew point increased the reservoir level also increased.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-018-23509-w">doi:10.1038/s41598-018-23509-w</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29581520">pmid:29581520</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5980089/">pmcid:PMC5980089</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qhktsz64y5ekrgu243nbmtnt5a">fatcat:qhktsz64y5ekrgu243nbmtnt5a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201106070535/https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1001&amp;context=iepubs" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/73/2a/732a5759a6b58aa48fc9a212efc37de544e361b5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-018-23509-w"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980089" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Machine learning techniques to predict daily rainfall amount

Chalachew Muluken Liyew, Haileyesus Amsaya Melese
<span title="">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pkhnkszyprhb3orbf6g7tqmgiu" style="color: black;">Journal of Big Data</a> </i> &nbsp;
The main objective of this study is to identify the relevant atmospheric features that cause rainfall and predict the intensity of daily rainfall using machine learning techniques.  ...  The result of the study revealed that the Extreme Gradient Boosting machine learning algorithm performed better than others.  ...  Acknowledgements We gratefully acknowledge the North West of Ethiopia Meteorology Agency for providing meteorological data, valuable information, and kind help for the completion of this study.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-021-00545-4">doi:10.1186/s40537-021-00545-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vwa74srjmbaptgywx7exjku5ae">fatcat:vwa74srjmbaptgywx7exjku5ae</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220211191451/https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00545-4.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d8/13/d81323ed96f9cfd86469be14aa6edb4396aa7a3b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-021-00545-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

A Machine Learning Based Model for Energy Usage Peak Prediction in Smart Farms

SaravanaKumar Venkatesan, Jonghyun Lim, Hoon Ko, Yongyun Cho
<span title="2022-01-11">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ikdpfme5h5egvnwtvvtjrnntyy" style="color: black;">Electronics</a> </i> &nbsp;
Purpose: This study proposes a machine learning-based prediction model for peak energy use by analyzing energy-related data collected from various environmental and growth devices in a smart paprika farm  ...  In particular, machine learning technologies with big data analysis are actively used as one of the most potent prediction methods supporting energy use in the smart farm.  ...  Dew point energy production The humidity of 40% RH at 20 • C equals 6.0 • C dew point temperature. With a short dew point control band, it's easy to control the environment and save energy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/electronics11020218">doi:10.3390/electronics11020218</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sukkue6r7ncghimyqarngsaxme">fatcat:sukkue6r7ncghimyqarngsaxme</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220504222502/https://mdpi-res.com/d_attachment/electronics/electronics-11-00218/article_deploy/electronics-11-00218.pdf?version=1641897993" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/32/c8/32c8299c15cbdcfa9bccf86d498c3b9f568cfd46.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/electronics11020218"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Airport Arrival Flow Prediction considering Meteorological Factors Based on Deep-Learning Methods

Zhao Yang, Yifan Wang, Jie Li, Liming Liu, Jiyang Ma, Yi Zhong, Min Xia
<span title="2020-10-26">2020</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/y3fh56bfunh5fgneywwba6d4ke" style="color: black;">Complexity</a> </i> &nbsp;
The model parameters are sequentially updated based on the recently collected data and the new predicting results.  ...  This study presents a combined Long Short-Term Memory and Extreme Gradient Boosting (LSTM-XGBoost) method for flight arrival flow prediction at the airport.  ...  Considering that, as input features, the temperature is highly positively related to dew point temperature and highly positively negatively to QNH, these two variables (dew point temperature and QNH) are  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2020/6309272">doi:10.1155/2020/6309272</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/des7sooicbbdxjm56cbobfrikm">fatcat:des7sooicbbdxjm56cbobfrikm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201031072415/http://downloads.hindawi.com/journals/complexity/2020/6309272.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/61/73/6173dd6467ecb62d70126c6cd820d29948e397cf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2020/6309272"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a>

Sea Fog Dissipation Prediction in Incheon Port and Haeundae Beach Using Machine Learning and Deep Learning

Jin-Hyun Han, Kuk-Jin Kim, Hyun-Seok Joo, Young-Hyun Han, Young-Taeg Kim, Seok-Jae Kwon
<span title="2021-08-02">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Next, we modeled fog dissipation using two separate algorithms, classification and regression, and a model with nine machine learning and three deep learning techniques.  ...  Sea fog is a natural phenomenon that reduces the visibility of manned vehicles and vessels that rely on the visual interpretation of traffic.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21155232">doi:10.3390/s21155232</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7njh6u3nwvelbp2tz5ebotzepy">fatcat:7njh6u3nwvelbp2tz5ebotzepy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210803044140/https://res.mdpi.com/d_attachment/sensors/sensors-21-05232/article_deploy/sensors-21-05232-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6d/a7/6da7bd55bbf5f1d01559ac3a069a13033dd32bfb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21155232"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Ambrosia Pollen

Gebreab K. Zewdie, David J. Lary, Estelle Levetin, Gemechu F. Garuma
<span title="2019-06-04">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vyslcn4ljzdq3jes5w7fln3qyu" style="color: black;">International Journal of Environmental Research and Public Health</a> </i> &nbsp;
Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts.  ...  The machine learning approaches used for developing a suite of empirical models are deep neural networks, extreme gradient boosting, random forests and Bayesian ridge regression methods for developing  ...  , surface albedo, total column ozone, volumetric soil water, dew point temperature at 2 m, surface and 2 m temperature and precipitation, high and low vegetation cover, etc.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijerph16111992">doi:10.3390/ijerph16111992</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kcccfejrcvfathnpyig74q5soy">fatcat:kcccfejrcvfathnpyig74q5soy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200214004527/https://res.mdpi.com/d_attachment/ijerph/ijerph-16-01992/article_deploy/ijerph-16-01992-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9d/e9/9de915a98e96764b956459a1ed8c94bf9db1ed18.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijerph16111992"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

Kai Zhang, Yun Li, Joel D. Schwartz, Marie S. O׳Neill
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ixhtx63uovbujgqpxilyyzxz6u" style="color: black;">Environmental Research</a> </i> &nbsp;
Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days.  ...  A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome.  ...  Acknowledgments The research described in this paper was funded through support of the Graham Environmental Sustainability Institute at the University of Michigan; the U.S.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.envres.2014.04.004">doi:10.1016/j.envres.2014.04.004</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/24834832">pmid:24834832</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4091921/">pmcid:PMC4091921</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7xs36vufczhblatry4sdkoljpa">fatcat:7xs36vufczhblatry4sdkoljpa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191114010052/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4091921&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/ac/a0ac0516bafd62fa2fea5537dac0d015b1d45142.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.envres.2014.04.004"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091921" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
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