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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems
Published 2017“…Unconstrained and constrained optimization problems with continuous design variables are used to illustrate the effectiveness and robustness of the proposed algorithm. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
Conference paper -
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer
Published 2024“…This necessitates advanced optimization approaches that can handle the added variability and constraints. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”
Conference paper -
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…In the FPSO method, the local search is performed through the modified light intensity attraction step with PSO operator. Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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A hybrid numerical approach for multi-responses optimization of process parameters and catalyst compositions in CO2 OCM process over CaO-MnO/CeO2 catalyst
Published 2005“…The hybrid numerical approach combined the single-response modeling and optimization using Response Surface Methodology (RSM) and WSSOF technique of multi-responses optimization. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes
Published 2020“…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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Book Chapter -
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Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation
Published 2018“…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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