Search Results - (( using optimization method algorithm ) OR ( using adaptive variable algorithm ))
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The proposed new algorithm has more optimal CR than the various variants of the Huffman-based lossless application. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…This motivates the researchers to investigate other methods. This thesis presents an investigation of using the Intelligent Water Drops (IWD) algorithm to construct and produce good quality solutions for the UETP. …”
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Evolutionary and population dynamics of 3 parents differential evolution (3PDE) using self-adaptive tuning methodologies
Published 2011“…As a result of the observed evolutionary dynamics, 3PDE-SAF performed the best among the preliminary proposed algorithms that included 3PDE-SACr and 3PDE-SACrF. Subsequently, 3PDE-SAF is chosen for the self-adaptive population size for testing dynamic population sizing methods using the absolute (3PDE-SAF-Abs) and relative (3PDE-SAF-Rel) population size encodings. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The algorithm is also preceded with careful seeding using mathematically proved to converge k-means++ algorithm. …”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer
Published 2024“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Modeling of hydrological process has been increasingly complicated since we need to take into consideration an increasing number of descriptive variables. In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization
Published 2022“…In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
Published 2015“…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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