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Neural Collaborative Reasoning [article]

Hanxiong Chen, Shaoyun Shi, Yunqi Li, Yongfeng Zhang
<span title="2020-06-11">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Inspired by recent progress on neural-symbolic machine learning, we propose a neural collaborative reasoning framework to integrate the power of embedding learning and logical reasoning, where the embeddings  ...  Collaborative Filtering (CF) has been an important approach to recommender systems.  ...  To achieve this goal, we propose neural collaborative reasoning, which defines the recommendation problem as a differentiable (i.e., neural) logical reasoning problem based on the wisdom of the crowd (  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.08129v3">arXiv:2005.08129v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x7plofpyl5drrcmhhnygpcwmmq">fatcat:x7plofpyl5drrcmhhnygpcwmmq</a> </span>
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Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge [article]

Guangli Li, Lei Liu, Xueying Wang, Xiao Dong, Peng Zhao, Xiaobing Feng
<span title="2018-12-16">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
By analyzing the characteristics of layers in DNNs, an auto-tuning neural network quantization framework for collaborative inference is proposed.  ...  The experimental results show that our framework can generate reasonable network partitions and reduce the storage on mobile devices with trivial loss of accuracy.  ...  We illustrate the most reasonable partition for each neural network.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1812.06426v1">arXiv:1812.06426v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n5enbxjoo5dzphvahfzlrmgatq">fatcat:n5enbxjoo5dzphvahfzlrmgatq</a> </span>
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Analyzing and forecasting the global CO2 concentration – a collaborative fuzzy–neural agent network approach

T. Chen
<span title="">2015</span> <i title="Universidad Nacional Autonoma de Mexico"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nzjmkf64dneihfgisybqfad65i" style="color: black;">Journal of Applied Research and Technology</a> </i> &nbsp;
In the collaborative fuzzy-neural agent network, a group of autonomous agents is used.  ...  The real data were used to evaluate the effectiveness of the collaborative fuzzy-neural agent network approach. All Rights Reserved  ...  Forecasting the Global CO 2 Concentration Using the FBPN Reasoning Module In the collaborative fuzzy-neural agent network, each agent uses the FBPN reasoning module to forecast the global CO 2 concentration  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jart.2015.07.002">doi:10.1016/j.jart.2015.07.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bx6b4ykmp5b6dctjbhdr3xb7qa">fatcat:bx6b4ykmp5b6dctjbhdr3xb7qa</a> </span>
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Antenatal diagnosis of neural tube defects in Canada: extension of a collaborative study

N E Simpson, L Dallaire, J R Miller, L Siminovitch, J Miller, J L Hamerton
<span title="1979-03-17">1979</span> <i title="Canadian Medical Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a64bbeloh5gblcelpcmohp322u" style="color: black;">Canadian Medical Association Journal</a> </i> &nbsp;
other reasons was 0.3%.  ...  This suggests that the AFP concentration should be measured in any sample of amniotic fluid collected for other reasons (usually fetal karyotyping).  ...  for other reasons was 0.3"/o.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/86382">pmid:86382</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC1819155/">pmcid:PMC1819155</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yclyvhef4ncyxf6aferjasgwmy">fatcat:yclyvhef4ncyxf6aferjasgwmy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200430112435/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC1819155&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/0b/49/0b49a2e3d617b29a0539379d69e434a4d895820e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1819155" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Introduction to cognitive artificial systems

Antonio Lieto, Marco Cruciani
<span title="2015-04-03">2015</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hvjabg6rlbfzvikzau6kwkjaqi" style="color: black;">Connection science</a> </i> &nbsp;
The paper "A Knowledge-Based System for Prototypical Reasoning", by Antonio Lieto, Andrea Minieri, Alberto Piana and Daniele P.  ...  neural computational power cannot explain the (artificial) cognition which emerged throughout adaptive processes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/09540091.2015.1007700">doi:10.1080/09540091.2015.1007700</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hjqi5w2kwbb6pbk2tbnulb44ym">fatcat:hjqi5w2kwbb6pbk2tbnulb44ym</a> </span>
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Improvement of Crop Production Using Recommender System by Weather Forecasts

S. Bangaru Kamatchi, R. Parvathi
<span title="">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cx3f4s3qmfe6bg4qvuy2cxezyu" style="color: black;">Procedia Computer Science</a> </i> &nbsp;
Artificial Neural Networks possess the capability of not just analysing the data but also learning from the data.  ...  Artificial Neural Networks possess the capability of not just analysing the data but also learning from the data.  ...  The research build's a system capable of suggesting the new users via collaborative filtering and methods in CBR (case-based reasoning).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.procs.2020.01.023">doi:10.1016/j.procs.2020.01.023</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eudufc656zbb7e5soxj2zn5pq4">fatcat:eudufc656zbb7e5soxj2zn5pq4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200301213224/https://pdf.sciencedirectassets.com/280203/1-s2.0-S1877050920X00032/1-s2.0-S1877050920300314/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEEYaCXVzLWVhc3QtMSJIMEYCIQDnbH3Zulkc5PgbpnTiwgLqmsh3wdtA5qS4tcoM6VWq8gIhAMCaiTuDanTF0bASYlr4fo20sOzIpDNexWlnEGAlNRDeKrQDCB4QAhoMMDU5MDAzNTQ2ODY1IgwyjDUX8qVlN1OiyNAqkQNl3gZ6mu%2FEg8iXXgeOBm8ynGo85El%2Bo19AAu1yVMxBlbZpyDNnJClAZRA9NgiXAmQPaDn00%2F8glYAMbynQegXXq2t5mgU3plxOzp%2Fvoc%2BrOYcVYUMRAkGZLck5J%2BA%2B0DgiJ47UaAMcIedbQ0EetSqZLCrgviAM%2BE4b3LTophducxuFe0UaGP1Go1yTGZLKBcyjhtydJgyVRWMOoymIiLTCd7yuJ8XtNePVturVu1zIdn9OUjNfxKQeMtQAB3%2B2DFBZQVA2X8I2qdhSvWd7iz%2FvqyEZi6boMX2wZo9bJOkfP%2FfuX02E1pDjVz%2F2isXeIb8y4YNJ8kwi9ABdwNpZOIUzyfbj%2BNUL48z9Bx5vAYDw3ujn%2FO3NReeojRXzOs2oyyEkBNoHD6Wc6g7ICJC3wVjUTCCEMK%2BzAEj4Z8AzqS0o2vkpTG6et8i9PoDjuRLt3eGODWGOBxs8sP%2FWfP%2BP4CQp4pI963Mm%2FYaRKLHI6TyTuI4Fp7I%2FUS1bx%2B4wDVePvgvR2HkuZYxC%2BQUjwixIOnScczDDzPDyBTrqAaILz%2F0MK0c%2F2QYJSalURJ1JudUMRAEYHk74%2BLZHiIHOo39j5TqY2VLOUqofMkdy4Is2hGMdJ6PqqUMUVGc3WFi2lBI5J2B88ia5qQUrY%2Bcn4lwGz2oKQbEyxgIi5T9mndZ3z1Vkv2CS%2FPycHQ6c6Jo7MmHRFJ7xXACq12erN08mov3Ki1malL2iBDcCcooBCpt673yl5gHMAeAFCKh0C8sG9tCj0T9DR4QYMzIpdQFJN1rcOgFWGUU24WuXlb3%2FHfmNSHiAdY3LPcNyufmfDXybTZ%2F2RBQcjbfiQQp%2BEiANu%2BmzQ6t%2BbmmjOQ%3D%3D&amp;X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20200301T213218Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=300&amp;X-Amz-Credential=ASIAQ3PHCVTY34VTVRTE%2F20200301%2Fus-east-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=db30680c84b3485da6840ced3f17f1579a190e6130bee6fdd8926ef102a65ea2&amp;hash=f7004d61d1ba8178132acab557b96723f306db53b70bc18bb050f2152453b1c0&amp;host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&amp;pii=S1877050920300314&amp;tid=spdf-8595fb33-bb88-4b74-91b7-d212bf3601c2&amp;sid=6a13be2d7ade90484c2a47043db8536e73ebgxrqa&amp;type=client" 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] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.procs.2020.01.023"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

RECOMMENDER SYSTEMS BASED ON DEEP LEARNING

Xushbaqov Sherzod, Khamraev Mansur, Bakhtiyorova Mokhiruy
<span title="2022-04-23">2022</span> <i title="Zenodo"> Zenodo </i> &nbsp;
Then, the details of deep learning-based collaborative filtering recommender systems are provided.  ...  Recurrent neural network-based collaborative filtering method Recurrent neural network (RNN) is suitable for modelling sequential data.  ...  The result of the model training is to get the weights between the neurons of deep neural network. It is difficult to give a reasonable explanation directly to the recommendation results.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.6473945">doi:10.5281/zenodo.6473945</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kwzv2uc25ngjzg5sxver7yp2ke">fatcat:kwzv2uc25ngjzg5sxver7yp2ke</a> </span>
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Can co-authorship networks be used to predict author research impact? A machine-learning based analysis within the field of degenerative cervical myelopathy research

Noah Grodzinski, Ben Grodzinski, Benjamin M Davies
<span title="2021-09-02">2021</span> <i title="Public Library of Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
Analysis of the neural network shows that the nature of collaboration strongly impacts an author's research visibility, and therefore suitability as a KOL.  ...  The neural network was retrospectively validated on an unseen author set.  ...  Secondly, the neural network was trained on H-Index. This is not an ideal impact metric (for reasons already outlined), but was included as a widely used, quantitative surrogate of research impact.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0256997">doi:10.1371/journal.pone.0256997</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34473796">pmid:34473796</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8412256/">pmcid:PMC8412256</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/su5gdbagvvdtrnwfickldav6ci">fatcat:su5gdbagvvdtrnwfickldav6ci</a> </span>
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Neurocomputing research in The Netherlands

H. Kappen, C. Gielen
<span title="">1990</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bby322qx6ndsje4ypr56c7nnly" style="color: black;">Neurocomputing</a> </i> &nbsp;
Most neural network research in The Netherlands collaborates through this program.  ...  However, considerable effort on biological neural networks is done at several universities. This interdisciplinary collaboration with biologists, physicists and  ...  mathematicians, which has been developed within the Foundation for Biophysics, will continue to provide an active collaboration in the future.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/0925-2312(90)90015-j">doi:10.1016/0925-2312(90)90015-j</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/drhcdmfkubccnalwvbfwfxlu5e">fatcat:drhcdmfkubccnalwvbfwfxlu5e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200313022550/https://repository.ubn.ru.nl/bitstream/handle/2066/166892/166892.pdf;jsessionid=81659404FDC391351092808FE2A5D6FF?sequence=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/23/1d/231d1025f3c8bc393c188cab54d22f9dfcca5f48.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/0925-2312(90)90015-j"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

The Case for a Mixed-Initiative Collaborative Neuroevolution Approach [article]

Sebastian Risi, Jinhong Zhang, Rasmus Taarnby, Peter Greve, Jan Piskur, Antonios Liapis, Julian Togelius
<span title="2014-08-05">2014</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Therefore, in this paper we argue for a mixed-initiative approach for collaborative online brain building and present first results towards this goal.  ...  It is clear that the current attempts at using algorithms to create artificial neural networks have had mixed success at best when it comes to creating large networks and/or complex behavior.  ...  The reasons for this are manifold.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1408.0998v1">arXiv:1408.0998v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n2upyxcyjjbc7itcczyvj2ftdq">fatcat:n2upyxcyjjbc7itcczyvj2ftdq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200925055615/https://arxiv.org/pdf/1408.0998v1.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/df/85/df85bf1a97da9632309cc88c464f9a74ac175ac3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1408.0998v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Special issue editorial on advances in collaborative systems engineering for product design, production and service network

Amy J. C. Trappey, Weiming Shen, John Jianzhong Cha
<span title="2016-05-14">2016</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gztrxqyspbbbngdnborbynzrmi" style="color: black;">Journal of Systems Science and Systems Engineering</a> </i> &nbsp;
They focus on solving challenging issues for enabling the production and service collaborations and their systems, e.g., multi-node tracking for wireless sensor network, agent-based neural network system  ...  systems, i.e., for product design collaborations and for production and service network collaborations.  ...  neural network system for failure prediction, one-stop logistic services for collaborative supply chain, and system maintainability analysis for complex collaboration.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11518-016-5313-5">doi:10.1007/s11518-016-5313-5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/56dgrkbmvjhpbb3inm64urgrkq">fatcat:56dgrkbmvjhpbb3inm64urgrkq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181030102936/https://link.springer.com/content/pdf/10.1007%2Fs11518-016-5313-5.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/0a/86/0a862aee29ad4fabc5c77d77c3cc49e1c02b7a5f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11518-016-5313-5"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Content-Aware Collaborative Music Recommendation Using Pre-Trained Neural Networks

Dawen Liang, Minshu Zhan, Daniel P. W. Ellis
<span title="2015-10-26">2015</span> <i title="Zenodo"> Zenodo </i> &nbsp;
This is not surprising for two reasons: 1) Here we treat tag prediction as a supervised task and train a multi-layer neural network, while in [10] the problem is formulated as an unsupervised learning  ...  [15] also use a neural network to incorporate music content into the collaborative filtering model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.1416308">doi:10.5281/zenodo.1416308</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/grpfm3xuefhllhc5lv6kmpxdly">fatcat:grpfm3xuefhllhc5lv6kmpxdly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200216145829/https://zenodo.org/record/1416308/files/LiangZE15.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/6e/06/6e06a1796bf36b2f0896a3e350a972e3160c7d66.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.1416308"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Recurrent Neural Networks for real-time distributed collaborative prognostics

Adria Salvador Palau, Kshitij Bakliwal, Maharshi Harshadbhai Dhada, Tim Pearce, Ajith Kumar Parlikad
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fudl6qe3nffxrcsbnnnb2v4dni" style="color: black;">2018 IEEE International Conference on Prognostics and Health Management (ICPHM)</a> </i> &nbsp;
We present the first steps towards real-time distributed collaborative prognostics enabled by an implementation of the Weibull Time To Event -Recurrent Neural Network (WTTE-RNN) algorithm.  ...  We show how through collaboration between assets and distributed prognostics, competitive time to failure estimates can be obtained. 1  ...  less than 30 minutes with reasonable accuracy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icphm.2018.8448622">doi:10.1109/icphm.2018.8448622</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icphm/PalauBDPP18.html">dblp:conf/icphm/PalauBDPP18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cxhvibcxfbbjbaqcqdzg4exz2u">fatcat:cxhvibcxfbbjbaqcqdzg4exz2u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430211128/https://www.repository.cam.ac.uk/bitstream/handle/1810/279246/2018_PHM.pdf;jsessionid=9C0E207A1CD112BC7C1D3046025302CE?sequence=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/76/8f/768ff10a37c7e5229711d1897402b6d79aa78a05.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icphm.2018.8448622"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Key Technologies of Collaborative Design and Manufacturing of Mechanical and Electrical Products Based on Internet of Things

Kun Shang, Sang-Bing Tsai
<span title="2021-10-04">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/khqygtfojnby3jyh5obuwd7ko4" style="color: black;">Mobile Information Systems</a> </i> &nbsp;
In this paper, the application of collaborative design and manufacturing in the design automation of IOT electromechanical system is reviewed, and the application of collaborative design and manufacturing  ...  with the conventional RBF neural network controller.  ...  1.68 4.32 1.17 4.86 2.77 Humidity 4.95 4.58 3.96 3.19 3.97 Flow 1.59 6.39 1.56 3.94 1.81 0 2 4 6 8 Design speed Neural Networks Fuzzy reasoning Decision tree design  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/8936762">doi:10.1155/2021/8936762</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cdqgra72c5d4pfb2oppe6rpi7u">fatcat:cdqgra72c5d4pfb2oppe6rpi7u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211005035628/https://downloads.hindawi.com/journals/misy/2021/8936762.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/c8/66/c866da68d1779be579f0dd21fd580bc1f85c3d04.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/8936762"> <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>

Link prediction in author collaboration network based on BP neural network

Chaoqun Chen, Sanhong Deng, Jing Lu, Bing Xu, Yinong Chen
<span title="">2017</span> <i title="EDP Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4vlgvitw6fcmbay5hkyo2s2ime" style="color: black;">MATEC Web of Conferences</a> </i> &nbsp;
The experiment shows that the BP neural network can get better result, and it is feasible to predict links in the author collaboration network. the task of link prediction is divided into two categories  ...  After data cleaning, the training set and test set are constructed and then used BP neural network to build model.  ...  Therefore, it is reasonable to apply BP neural network to link prediction in social network. Of course, there are deficiencies in this article.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/matecconf/201713900073">doi:10.1051/matecconf/201713900073</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u5vt4h2ukve35ivswlspy6if4m">fatcat:u5vt4h2ukve35ivswlspy6if4m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180724101505/https://www.matec-conferences.org/articles/matecconf/pdf/2017/53/matecconf_icmite2017_00073.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/3a/4d/3a4d01797ad8b876db22b5910e8011d336cba0e7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/matecconf/201713900073"> <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>
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