Search Results - (( evolution optimization parallel algorithm ) OR ( policy implementation learning algorithm ))
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…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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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…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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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…Although the research is limited with respect to its sample size and geographical scope, it has provided important findings that can be used when implementing data-driven methods in social policy formulation and poverty mitigation strategies.…”
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Deep Reinforcement Learning For Control
Published 2021“…As a result, the simulation environment makes it possible to collect massive training datasets. Improving learning driving policies can be adopted fast in the actual world. …”
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Ethical considerations for equitable outcome-based education in the Metaverse: a qualitative study
Published 2025“…Semi-structured interviews were conducted with 11 XR experts across education, design, and policy domains. Thematic analysis revealed three primary ethical concerns: digital access inequities, bias in assessment algorithms, and privacy and data governance risk. …”
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Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic
Published 2022“…It will be of great significance for the introduction and implementation of national policies.…”
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Ethical considerations for equitable outcome-based education in the metaverse: a qualitative study
Published 2025“…Semi-structured interviews were conducted with 11 XR experts across education, design, and policy domains. Thematic analysis revealed three primary ethical concerns: digital access inequities, bias in assessment algorithms, and privacy and data governance risk. …”
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Comparison of PPO and SAC Algorithms towards decision making strategies for collision avoidance among multiple autonomous vehicles
Published 2021“…In order to address this challenge, a simulation was implemented in the Unity3D game engine and two state-of-the-art RL algorithms PPO (Proximal Policy Optimization) and SAC (Soft Actor-Critic) were trained by an agent using Unity ML-Agents Toolkit. …”
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Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024)
Published 2025“…This model serves as a practical guide for educators and stakeholders aiming to implement AI-enhanced pedagogies responsibly. Ultimately, the study underscores the need for interdisciplinary collaboration among educators, policymakers, and technology developers to foster sustainable and inclusive learning environments. …”
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Poverty Classification in Indonesia Using BiGRU, BPNN, and Stacking AdaBoost Frameworks
Published 2024“…These findings underscore the critical role of machine learning in formulating effective policies for poverty alleviation and suggest that integrating multiple machine learning algorithm can significantly enhance decision-making processes. …”
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Flow-based approach on bro intrusion detection
Published 2017“…Then, the model made use the machine learning classification algorithms for attribute evaluation and Bro policy scripts for detecting malicious flows. …”
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