Search Results - (( developing function search algorithm ) OR ( learning object optimization algorithm ))
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
Published 2023Conference Paper -
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Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index
Published 2023“…Electric power plant loads; Learning algorithms; MATLAB; Multiobjective optimization; Optimization; Reactive power; Back tracking; Backtracking search algorithms; Identification method; Load-shedding; Multi-objective functions; Power flow simulation; System contingencies; Under voltage load shedding; Electric load shedding…”
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control
Published 2025“…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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Pseudo Randomized Search Strategy (PRSS*) of the ambiguity function mapping
Published 1998“…A combination between three methods of optimization, global random search and ambiguity function mapping produced an efficient search algorithm what the author called the Pseudo Randomized Search Strategy (PRSS). …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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A Quantum Lightning Search Algorithm-Based Fuzzy Speed Controller for Induction Motor Drive
Published 2023Article -
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A Stepper Motor Design Optimization Using
Published 2005“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Monograph -
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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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Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system
Published 2022“…This paper presents an improved version of Manta Ray Foraging Optimization (MRFO). MRFO is relatively a single objective optimization algorithm. …”
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Conference or Workshop Item -
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Manta ray foraging optimization with quasi-reflected opposition strategy for global optimization
Published 2022“…MRFO is a new algorithm that developed based on the nature of a species in cartilaginous fish called Manta Ray. …”
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Text searching algorithm using boyer moore horspool (BMH) algorithm
Published 2015“…The objective of this study is to develop a searching function using Boyer-Moore Horspool algorithm based on keyword in a medical database. …”
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Undergraduates Project Papers -
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Design of intelligent control system and its application on fabricated conveyor belt grain dryer
Published 2011“…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems
Published 2022“…The current major existing multi-objective recommendation approaches utilize collaborative filtering method as rating predictor to replenish the missing ratings and combined with evolutionary algorithm for only bi-objective optimization. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…There are three objectives in this research. The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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