Titlebook: Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems; Essam Halim Houssein,Mohamed Abd Elaziz,Laith Abua

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Metaheuristics for Parameter Estimation of Solar Photovoltaic Cells: A Comprehensive Review,s, they are considered environment friendly, green, safe and sustainable power sources. The use of solar radiation is increasing as a clean source of energy. The Photovoltaic (PV) panels that contain solar cells are used to transform the solar energy into electricity. This article discusses and expl

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Big Data Analysis Using Hybrid Meta-Heuristic Optimization Algorithm and MapReduce Framework,hers. In order to manage the rapidly growing data sizes, traditional clustering algorithms must be improved. In this research, a hybrid Harris Hawks Optimizer (HHHO) with K-mean clustering and MapReduce framework is proposed to solve the various data clustering problem. The proposed scheme uses the

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Deep Neural Network for Virus Mutation Prediction: A Comprehensive Review,emic safety, they have become an integrative part of the modern scientific methodology, offering automated procedures for the prediction of a phenomenon based on past observations, unraveling underlying patterns in data and providing insights about the problem. With the continuous growth in the numb

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Hybrid Adaptive Moth-Flame Optimizer and Opposition-Based Learning for Training Multilayer Perceptre moths’ navigation behavior and dynamic coefficients. However, such a basic version can be easily trapped in the local optima and is associated with an unstable balance between exploratory and exploitative cores. To mitigate the shortcomings of slow convergence and local stagnation, an adaptive mot

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Review for Meta-Heuristic Optimization Propels Machine Learning Computations Execution on Spam Commenchmark cutoff focuses or essential setting-centered evaluations. To visually examine the commencement of techniques procured for smoothing out those conditions, scientists and experts felt a need to agnize the difficulties and break harmonious changes, modifications, and amendments in the evaluati

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Parameter Tuning of PID Controller Based on Arithmetic Optimization Algorithm in IOT Systems,ential device in most engineering applications. The vital abuse of PID is choosing the best parameters‘ values (K., K., and K.) with the traditional methods which cannot achieve the optimum response. In this work, Arithmetic Optimization Algorithm (AOA) which is a meta-heuristic algorithm is used to

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Testing and Analysis of Predictive Capabilities of Machine Learning Algorithms, of research and business. However, identifying the appropriate algorithm for a particular program has always been an enigma, and that necessitates to be solved ere the development of any machine learning system. Let’s take the example of the weather forecasting prediction system, it is used to iden