Search Results - (( factor objective evolutionary algorithm ) OR ( java application learning algorithm ))
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Fuzzy optimization with multi-objective evolutionary algorithms: A case study
Published 2007“…On the other hand, an ad hoc Pareto-based multi-objective evolutionary algorithm to capture multiple non dominated solutions in a single run of the algorithm is described. …”
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Integrated Grasshopper Algorithm-Evolutionary Programming Technique for Distributed Energy Resources Allocation
Published 2023Conference Paper -
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023“…In this study, multi-objectives genetic algorithm (MOGA) is utilized due to there are more than one objective need to be achieved while planning for the robot moving path. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Multi-objective optimization of HRES by Evolutionary Algorithm have become attractive in recent years due to the effectiveness of such algorithms for complicated problems. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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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 thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi
Published 2014“…This proposed technique will be compared with Evolutionary Programming (EP) algorithm, that usually designed to maximize or minimize the objective function, which is a measure of the quality of each candidate solution. …”
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Bacterial foraging optimization algorithm for optimal load shedding in power systems / Wan Nur Eliana Afif Wan Afandie
Published 2016“…By using Bacterial Foraging Optimization Algorithm (BFOA) technique, for each types of load shedding, the simulations are tested on IEEE 30-bus system for 3 and 5 load shedding locations. 3 different load conditions and one line outage cases are tested for 3 objective function and 3 multi-objective functions. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…The simulation results indicate that the algorithm is able to segregate and assign the tasks for each scanning head and also able to find the shortest scanning path for different types of objects coordination. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization
Published 2025“…The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization
Published 2025“…The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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Effect of multi-unit and multi-type DG installation using integrated optimization technique in distribution power system planning
Published 2025“…It handles various scenarios, including multi-DG single-type and multi-DG multi-type installations, with the main objective of minimizing power loss in the system. This technique employs a hybrid approach that combines elements of immune algorithms, moth flame optimization, and evolutionary programming to achieve more accurate and efficient results. …”
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