Search Results - (( intelligence based ems algorithm ) OR ( intelligence based ((bee algorithm) OR (_ algorithm)) ))
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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
Published 2025“…EMS strategies; AI-based algorithms categories, functions and hybridization; the state-of-art and future direction of AI-based algorithms and HFCEVs? …”
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EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency
Published 2016“…A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. …”
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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Final Year Project -
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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New Energy Management System Based on Intelligent Digital Power Monitoring
Published 2009“…This paper introduces a new Energy Management System (EMS) based on intelligent digital power monitoring. …”
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Optimal design of step – cone pulley problem using the bees algorithm
Published 2021“…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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Book Chapter -
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Energy Management Strategy (EMS) for Hybrid Electric Vehicles base on Safe Experimentation Dynamics (SED)
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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Employing Artificial Intelligence to Minimize Internet Fraud
Published 2009“…Today, pre-empting or preventing fraud before it happens occurs in the manual, non-computer based business transactions because of the natural intelligence of both seller and buyer. …”
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A Hybrid Soft Computing Framework for Electrical Energy Optimization
Published 2021“…In this paper, a hybrid soft-computing-based framework has been proposed for intelligent energy management and optimization. …”
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Energy Management System For Three-Wheel Light Electric Vehicle Using Multi-Sources Energy Models
Published 2016“…A rule-based control algorithm which contains eight states in EMS is designed to control power switches and to ensure sufficient energy is delivered to the load. …”
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Thesis -
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Algorithm in the fluidized-bed reactor for the polymerization of propylene
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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Thesis -
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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A quick gbest guided artificial bee colony algorithm for stock market prices prediction
Published 2018“…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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