Evolutionary machine learning techniques algorithms and applications

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Weitere Verfasser: Mirjalili, Seyedali (HerausgeberIn), Faris, Hossam (HerausgeberIn), Aljarah, Ibrahim (HerausgeberIn)
Format: Buch
Sprache:English
Veröffentlicht: Singapore Springer [2020]
Schriftenreihe:Algorithms for intelligent systems
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Datensatz im Suchindex

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adam_text Contents Introduction to Evolutionary Machine Learning Techniques................... Seyedali Mirjalili, Hossam Fans and Ibrahim Aljarah 1 Classification and Predication Salp Chain-Based Optimization of Support Vector Machines and Feature Weighting for Medical Diagnostic Information Systems............ Ala’ M. Al-Zoubi, Ali Asghar Heidari, Maria Habib, Hossam Faris, Ibrahim Aljarah and Mohammad A. Hassonah Support Vector Machine: Applications and Improvements Using Evolutionary Algorithms...................................................................... Seyed Hamed Hashemi Mehne and Seyedali Mirjalili Efficient Moth-Flame-Based Neuroevolution Models................................. Ali Asghar Heidari, Yingyu Yin, Majdi Mafarja, Seyed Mohammad Jafar Jalali, Jin Song Dong and Seyedali Mirjalili Autonomous Robot Navigation Using Moth-Flame-Based Neuroevolution.................................................................................................... Seyed Mohammad Jafar Jalali, Rachid Hedjam, Abbas Khosravi, Ali Asghar Heidari, Seyedali Mirjalili and Saeid Nahavandi Link Prediction Using Evolutionary Neural Network Models................ Rawan I. Yaghi, Hossam Faris, Ibrahim Aljarah, Ala’ M. Al֊Zoubi, Ali Asghar Heidari and Seyedali Mirjalili Evolving Genetic Programming Models for Predicting Quantities of Adhesive Wear in Low and Medium Carbon Steel.............................. Rana Faris, Bara’a Almasri, Hossam Faris, Faris M. AL-Oqla and Doraid Dalalah 11 35 51 67 85 113 vii viü Contents Feature Selection EvoloPy-FS: An Open-Source Nature-Inspired Optimization Framework in Python for Feature Selection................................................. Ruba Abu Khurma, Ibrahim Aljarah, Ahmad Sharieh and Seyedali Mirj alili Multi-objective Particle Swarm Optimization: Theory, Literature Review, and Application in Feature Selection for Medical Diagnosis.............................................................................................................. Maria Habib, Ibrahim Aljarah, Hossam Faris and Seyedali Mirjalili Multi-objective Particle Swarm Optimization for Botnet Detection in Internet of Things......................................................................................... Maria Habib, Ibrahim Aljarah, Hossam Faris and Seyedali Mitjalili 131 175 203 Evolutionary and Swarm-Based Feature Selection for Imbalanced Data Classification.............................................................................................. 231 Feras Namous, Hossam Faris, Ali Asghar Heidari, Monther Khalafat, Rami S. Alkhawaldeh and Nazeeh Ghatasheh Binary Harris Hawks Optimizer for High-Dimensional, Low Sample Size Feature Selection......................................................................................... Thaer Thaher, Ali Asghar Heidari, Majdi Mafaija, Jin Song Dong and Seyedali Mirjalili A Review of Grey Wolf Optimizer-Based Feature Selection Methods for Classification.................................................................................................. Qasem Al-Tashi, Helmi Md Rais, Said Jadid Abdulkadir, Seyedali Mirjalili and Hitham Alhussian 251 273 Algorithms for Intelligent Systems Series Editors: Jagdish Chand Bansal · Kusum Deep · Atulya K. Nagar Seyedali Mirjalili · Hossam Fans · Ibrahim Aljarah Editors Evolutionary Machine Learning Techniques Algorithms and Applications This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fiizzy networks, modular neural net­ works, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse opti­ mizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
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series2 Algorithms for intelligent systems
spellingShingle Evolutionary machine learning techniques algorithms and applications
Maschinelles Lernen (DE-588)4193754-5 gnd
Künstliche Intelligenz (DE-588)4033447-8 gnd
subject_GND (DE-588)4193754-5
(DE-588)4033447-8
(DE-588)4143413-4
title Evolutionary machine learning techniques algorithms and applications
title_auth Evolutionary machine learning techniques algorithms and applications
title_exact_search Evolutionary machine learning techniques algorithms and applications
title_full Evolutionary machine learning techniques algorithms and applications Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah (editors)
title_fullStr Evolutionary machine learning techniques algorithms and applications Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah (editors)
title_full_unstemmed Evolutionary machine learning techniques algorithms and applications Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah (editors)
title_short Evolutionary machine learning techniques
title_sort evolutionary machine learning techniques algorithms and applications
title_sub algorithms and applications
topic Maschinelles Lernen (DE-588)4193754-5 gnd
Künstliche Intelligenz (DE-588)4033447-8 gnd
topic_facet Maschinelles Lernen
Künstliche Intelligenz
Aufsatzsammlung
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