Search Results - (( evolution solution learning algorithm ) OR ( program implementation force algorithm ))
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1
Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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3
Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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4
Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Dual optimization approach in discrete Hopfield neural network
Published 2024“…To evaluate the effectiveness of the Hybrid Differential Evolution Algorithm and Swarm Mutation in the learning and retrieval phases, several performance metrics are employed in terms of synaptic weight management, learning errors, testing errors, energy profiles, solution variations, and similarity for 10 different cases. …”
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7
Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023Conference Paper -
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Crossover and mutation operators of genetic algorithms
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Crossover and mutation operators of genetic algorithms
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Genetic algorithm based for optimizing filter design / Rohana Awang Ahmed
Published 2000“…The conventional filter design technique is adapted in writing a MATLAB program using the Signal Processing Toolbox. GA is then implemented using the Genetic Algorithm Toolbox (GAOT). …”
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13
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…To verify our proposed approach, four Arabic benchmark datasets for sentiment analysis are used since there are only a few studies in sentiment analysis conducted for Arabic language as compared to English. The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution
Published 2018“…This approach improves the flexibility of the ESNN algorithm in producing better solutions which is utilized to conquer the K-means disadvantages. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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17
Modular motor driver with torque control for gripping mechanism
Published 2023“…This is possible by taking in the magnitude of the current drawn by the load as the feedback to the system and set appropriate action to protect the system from damage when a certain setpoint of current is reached. In implementing the project, several algorithms were tested to achieve the torque control algorithm requirement including on-off algorithm, P algorithm, PI algorithm, PD algorithm and PID algorithm. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…Unfortunately, these algorithms suffer with several drawbacks such as the tendency to be trapped or stagnate into local optima and slow convergence rates. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…Hence, in this work, we design an improved Grasshopper Optimization Algorithm (GOA) based ESN. The proposed technique uses a new solution representation with a simplified attraction and repulsion mechanisms to enhance performance. …”
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Two-axis position-based impedance control of a 2-DOF robotic finger / Khairunnisa Nasir
Published 2017“…The positionbased impedance control algorithm was designed by regulating the mechanical impedance of the robotic finger based on force measurements from the two embedded force sensors. …”
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