Search Results - (( evolution optimization bat algorithm ) OR ( wave optimization learning algorithm ))
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Multi-Swarm bat algorithm
Published 2023“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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Water wave optimization with deep learning driven smart grid stability prediction
Published 2022“…In this background, the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction (WWOODL-SGSP) model. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff
Published 2017“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling
Published 2023“…Electromagnetic wave emission; Meteorology; Microgrids; Particle swarm optimization (PSO); Scheduling; Solar energy; Solar power generation; Wind; Battery status; BPSO algorithms; Learning rates; Optimal energy; Optimal values; Solar irradiation; Sustainable resources; Virtual power plants (VPP); Neural networks…”
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Selective opposition based constrained barnacle mating optimization: Theory and applications
Published 2024“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.…”
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Route Optimization based on Clustering and Travelling Salesman Problem
Published 2022“…In this paper, comparison results between the original route taken by the driver and the proposed route based on optimization are conducted and reported. The unsupervised learning result was also achieved and reported in comparison results. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification
Published 2019“…Thus, we propose an adaptive multi-parent crossover Genetic Algorithm (GA) for optimizing the features used in classifying epileptic seizures. …”
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi
Published 2025“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Characterization of oil palm fruitlets using artificial neural network
Published 2014“…To further validate the generalization accuracy of the LSB_ANN, its performance was compared with that of a Multi-ANFIS network as well as those of three different ANN training algorithms: Levenberg Marquardt (LM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA). …”
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…To validate the classi¯ers and the proposed algorithm, two data sets were used, the ¯rst set represents voltage amplitudes of Lamb-waves produced and col- lected by sensors and actuators mounted on the surface of laminates contain di®erent arti¯cial damages. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…The results show that Coarse K-Nearest Neighbours is the optimal classifier that predicts MS regions at an exceptionally high accuracy, while Support Vector Machine Kernel is the optimal classifier that perfectly predicts the reflection surfaces. …”
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