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Clustered Logistic Regression Algorithm for Flight Delay Prediction
2021
Zenodo
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In this research, we present a simulation of cluster computing in virtual environment while implementing data mining algorithm to perform a prediction of flight delay. ...
Keywords—Cluster computing, clustered logistic regression, logistic regression, flight delay prediction, pyspark, apache spark. ...
In this research, HPCC is used to accelerate the computing performance for flight delay prediction. ...
doi:10.5281/zenodo.4602107
fatcat:h5xf4aqfwzew3hk3v6dkzlsrfu
Performance Evaluation of Random Forest Algorithm in Cluster Environment
2022
Zenodo
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The experiment will attempt to predict the flight delay by using random forest algorithm with apache spark as a framework for cluster computing. ...
Keywords—Cluster computing, random forest, flight delay prediction, pyspark, apache spark. ...
In this paper, random forest is used to predict the flight delay. ...
doi:10.5281/zenodo.5852758
fatcat:b7dtbq5ho5gfjfpinheaxv5ybe
The Use of Cluster Computing and Random Forest Algoritm for Flight Delay Prediction
2022
Zenodo
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The objective of this research is to assess the performance of data mining algorithm (random forest) when executed in cluster environment. In the simulation, we use 1 master and 3 workers node. ...
When cluster computing and data mining are consolidated, it will yield an exceptionally amazing technology whereby the handling time in data mining can be sped up by utilizing the strength of cluster processing ...
In this research, HPCC is used to accelerate the computing performance for flight delay prediction. ...
doi:10.5281/zenodo.6377015
fatcat:iehoajl7uzglllm3qyk665rrkq
Performance Evaluation of Linear Regression Algorithm in Cluster Environment
[article]
2020
arXiv
pre-print
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The experiment will attempt to predict the flight delay by using linear regression algorithm with apache spark as a framework for cluster computing. ...
In this paper, we are going to evaluate the performance of cluster computing by executing one of data mining techniques in the cluster environment. ...
In this paper, Linear Regression is used to predict the flight delay. ...
arXiv:2009.06497v1
fatcat:ifjvqp67hne2zg2cqmffyk54em
Analysis of Big Data to Locate Critical Factors for Flight Delays using Machine Learning Algorithms
機械学習アルゴリズムを用いた飛行遅延要因を突き止めるためのビッグデータ分析
2018
Nihon Joho Keiei Gakkaishi
機械学習アルゴリズムを用いた飛行遅延要因を突き止めるためのビッグデータ分析
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The join and balancing operation were performed to make data prepared for modeling. Data mining operations were executed on the data in the cloud using MapReduce programs to achieve scalability. ...
For our analysis, we used Microsoft Visual Studio and SQL Serverʼs Analysis Service for data mining and SQL Server for data cleaning. ...
doi:10.20627/jsim.38.2_20
fatcat:7ngbqlbunzbgni7vfkloxokgoi
Architecture for Intelligent Big Data Analysis based on Automatic Service Composition
2015
Services Transactions on Big Data
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In this paper we proposed a novel architecture to automate data analytics process using Nested Automatic Service Composition (NASC) and CRoss Industry Standard Platform for Data Mining (CRISP-DM) as main ...
Since CRISP-DM also a well-known data science process which can be used as innovative accumulator of multi-dimensional data sets. ...
We can choose a data-mining method for BDA and other necessary procedure using our experiences. CRoss Industry Standard Platform for Data Mining (CRISP-DM) is a useful standard for BDA. ...
doi:10.29268/stbd.2015.2.2.1
fatcat:yknslsscjjexhiaksac545iddy
Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning
[article]
2018
arXiv
pre-print
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However, this task is challenging because of the complexity involved in mining multi-dimensional heterogeneous time series data, the lack of time-step-wise annotation of events in a flight, and the lack ...
Current methods suffer from poor scalability to high dimensional time series data and are inefficient in capturing temporal behavior. ...
The authors would like to thank the subject matter experts Michael Stewart, Bryan Matthews and Robert Lawrence for their insightful comments and perspectives on the identified precursors. ...
arXiv:1710.04749v2
fatcat:olhun6kwine27k4znp4kduzfsm
Estimating Customer Lifetime Value Using Machine Learning Techniques
[chapter]
2018
Data Mining
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It is well known that the competition for high-value customers has become the core of airline profits. ...
However, the models that are used to calculate the value of customer life value remain controversial, and how to design a model that applies to airline company still needs to be explored. ...
CLV prediction accuracy Fit is the criterion suggested in the data-mining literature [39] [40] [41] for problems where the primary objective is making predictions that are as accurate as possible. ...
doi:10.5772/intechopen.76990
fatcat:7pjs27errrdn5dnyxtpvo67bpq
Aircraft Aviation System Environment Impact Factors Prediction using Machine Learning
2020
International journal of recent technology and engineering
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Probabilistic prediction algorithms applied to support decision systems in generating guidelines to enhance the Eco-friendly architectures of aerodromes as well as aircrafts. ...
The classifications performed in this paper over aircraft systems generate interesting measures to classify environmental scalable aircrafts in future with better eco-friendly technology. ...
ARM Rule generations for Aircraft services Association Rule mining algorithm Apriori applied over training data of aircraft services provided by airport. ...
doi:10.35940/ijrte.f8503.038620
fatcat:j6wv2vq2urcsdkrd25zx6yyuwu
Restricted Airspace Unit Identification Using Density-Based Spatial Clustering of Applications with Noise
2019
Sustainability
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This paper first calculates the departure delay and arrival delay of each flight by mining historical flight data. ...
The main objective is to identify the restricted airspace units by calculating the average delay time according to the accumulative delay time of airspace units and the accumulative delay flight. ...
By mining a large amount of flight data, key features are extracted, then a machine learning model is established to predict the flight delay. ...
doi:10.3390/su11215962
fatcat:pvoisnqaybavhoparsjos73o4i
Online Long-Term Trajectory Prediction Based on Mined Route Patterns
[chapter]
2020
Lecture Notes in Computer Science
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In this paper, we present a Big data framework for the prediction of streaming trajectory data by exploiting mined patterns of trajectories, allowing accurate long-term predictions with low latency. ...
Subsequently, the trajectory prediction algorithm exploits these patterns in order to prolong the temporal horizon of useful predictions. ...
Motivated by these challenges, we present a Big data solution for online trajectory prediction by exploiting mined patterns of trajectories from historical data sources. ...
doi:10.1007/978-3-030-38081-6_4
fatcat:6n5heoumwfguln3chpcp35uifm
A Novel Mapreduce Lift Association Rule Mining Algorithm (Mrlar) for Big Data
2016
International Journal of Advanced Computer Science and Applications
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Therefore, there is a vital need to scalable and parallel strategies for ARM based on Big Data approaches. ...
Big Data mining is an analytic process used to discover the hidden knowledge and patterns from a massive, complex, and multi-dimensional dataset. ...
Data mining approaches can be classified into two major models [11] : The descriptive data mining and the predictive data mining models. ...
doi:10.14569/ijacsa.2016.070321
fatcat:ll4coeutmrhmtj4w53kwjif5v4
Forecasting Flight Delays Using Clustered Models Based on Airport Networks
2020
IEEE transactions on intelligent transportation systems (Print)
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ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers and the editor for their valuable inputs. ...
The models are then applied individually to each airport data for predicting the airport's flight delays. ...
There is extensive work in these areas in the data mining and statistics literature. ...
doi:10.1109/tits.2020.2990960
fatcat:uo37cyvvifhuvp3lm2ubxwhzhe
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms
2013
Journal of Aerospace Information Systems
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The data mining techniques include scalable multiple kernel learning for largescale distributed anomaly detection. ...
A novel multivariate time series search algorithm is used to search for signatures of discovered anomalies on massive data sets. ...
We would also like to thank Irv Statler, Bob Lawrence, Mike Feary, Immanuel Barshi and the partner air carrier for providing data and expertise. ...
doi:10.2514/1.i010080
fatcat:gvy7djz5wzdhtksf4hut5zujxu
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms
2014
Journal of Aerospace Information Systems
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The data mining techniques include scalable multiple kernel learning for largescale distributed anomaly detection. ...
A novel multivariate time series search algorithm is used to search for signatures of discovered anomalies on massive data sets. ...
We would also like to thank Irv Statler, Bob Lawrence, Mike Feary, Immanuel Barshi and the partner air carrier for providing data and expertise. ...
doi:10.2514/1.i010211
fatcat:igwifmgmezbmpca7euxoac2gn4
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