Search Results - Application of Genetic Programming in Machine Learning

The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition by Felipe Campelo, Lucas S. Batista, Claus Aranha

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PID Tuning Using Differential Evolution With Success-Based Particle Adaptations by Victor Parque, Alaa Khalifa

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BinHOA: Efficient Binary Horse Herd Optimization Method for Feature Selection: Analysis and Validations by Dina A. Elmanakhly, Mohamed Saleh, Essam A. Rashed, Mohamed Abdel‐Basset

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Machine learning-based downscaling: application of multi-gene genetic programming for downscaling daily temperature at Dogonbadan, Iran, under CMIP6 scenarios by Niazkar, Majid, Goodarzi, Mohammad Reza, Fatehifar, Atiyeh, Abedi, Mohammad Javad

“…In this study, two machine learning (ML) models, named multi-gene genetic programming (MGGP…”
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Multi-variant differential evolution algorithm for feature selection by Somaia Awad Hassan, Ashraf Mohamed Hemeida, Salem Alkhalaf, Al-Attar Ali Mohamed, Tomonobu Senjyu

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PARAMETER ADAPTATION FOR ANT COLONY SYSTEM IN WIRELESS SENSOR NETWORK by Husna Jamal Abdul Nasir, Ku Ruhana Ku‐Mahamud, Eiji Kamioka

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Software review: the KNIME workflow environment and its applications in genetic programming and machine learning by O’Hagan, Steve, Kell, Douglas B.

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Hydrologically Informed Machine Learning for Rainfall‐Runoff Modeling: A Genetic Programming‐Based Toolkit for Automatic Model Induction by Chadalawada, Jayashree, Herath, H. M. V. V., Babovic, Vladan

“…Models of water resources systems are conceived to capture the underlying environmental dynamics occurring within watersheds. All such models can be regarded…”
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Balanced Cartesian Genetic Programming via migration and opposition-based learning: application to symbolic regression by Yazdani, Samaneh, Shanbehzadeh, Jamshid

“… Cartesian Genetic Programming (CGP) is a generalization of the graph based genetic programming…”
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Comparison of approaches for machine-learning optimization of neural networks for detecting gene-gene interactions in genetic epidemiology by Motsinger-Reif, Alison A., Dudek, Scott M., Hahn, Lance W., Ritchie, Marylyn D.

“… To solve this, machine‐learning approaches have been suggested to evolve the best NN architecture for a particular data set…”
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Predicting discharge coefficient of triangular labyrinth weir using extreme learning machine, artificial neural network and genetic programming by Karami, Hojat, Karimi, Sohrab, Bonakdari, Hossein, Shamshirband, Shahabodin

“…, artificial neural network (ANN), genetic programming (GP) and extreme learning machine (ELM)]. The calculated discharge coefficients were then compared with some experimental results…”
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Alzheimer’s disease diagnosis using genetic programming based on higher order spectra features by Nasrolahzadeh, Mahda, Rahnamayan, Shahryar, Haddadnia, Javad

“…) by utilizing genetic programming (GP) as data-driven evolutionary computation based modeling…”
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Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis by Amar, Yehia, Schweidtmann, Artur M, Deutsch, Paul, Cao, Liwei, Lapkin, Alexei

“… Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow…”
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Modeling the influence of lime on the unconfined compressive strength of reconstituted graded soil using advanced machine learning approaches for subgrade and liner applications by Guo, Xinghuang, Garcia, Cesar, Andrade Valle, Alexis Ivan, Onyelowe, Kennedy, Zarate Villacres, Andrea Natali, Ebid, Ahmed M., Hanandeh, Shadi

“… This present study explores the application of machine learning (ML) techniques, namely Genetic Programming (GP…”
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Explainable Artificial Intelligence by Genetic Programming: A Survey by Mei, Yi, Chen, Qi, Lensen, Andrew, Xue, Bing, Zhang, Mengjie

“… Genetic programming is a powerful evolutionary algorithm for machine learning. Compared with other standard machine learning models such as neural networks, the models…”
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Population Dynamics in Genetic Programming for Dynamic Symbolic Regression by Fleck, Philipp, Werth, Bernhard, Affenzeller, Michael

“…This paper investigates the application of genetic programming (GP) for dynamic symbolic regression (SR…”
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Predicting Marshall parameters of flexible pavement using support vector machine and genetic programming by Zhang, Weiguang, Khan, Adnan, Huyan, Ju, Zhong, Jingtao, Peng, Tianyi, Cheng, Hanglin

“…[Display omitted] •Developed SVM models to predict the Marshall parameters of base and wearing course.•Simplified expressions were derived to predict the…”
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A Novel General Feature Enhancement Method Based on Genetic Programming for Improving RF Circuit Fault Diagnosis Using Machine Learning by Wu, Kunping, Long, Bing, Bu, Zhiyuan, Wang, Jingyuan, Liu, Zhen

“… In this manuscript, a novel general feature enhancement method based on genetic programming (GP) is proposed to improve the machine learning-based RF circuit fault diagnosis…”
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MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS by Jerzy Balicki, Waldemar Korłub

“… For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming…”
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Multi-time Step Deterioration Prediction of Freeways Using Linear Regression and Machine Learning Approaches: A Case Study by Tran, Huu, Robert, Dilan, Gunarathna, Prageeth, Setunge, Sujeeva

“…) and genetic programming (GP) models. An industry dataset of spray seal freeways is used to demonstrate the application of the methodology developed in this study…”
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