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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments
Published 2006“…MALESAbrain1-3 is an intelligent algorithm which originally is designed for problem-based learning (PBL) environment. …”
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Heuristic factors in ant system algorithm for course timetabling problem
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The thesis also covers the basic principles and operation of IPFC, the modified Newton-Raphson power flow method and an overview of the three intelligent optimization techniques used in this thesis. …”
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Mathematical formulation of tabu search in combinatorial optimization
Published 2008“…Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. The main advantage of TS with respect to other conventional search is in the intelligent use of past history of the search to influence its future search procedures. …”
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An Intelligent System Approach to the Dynamic Hybrid Robot Control
Published 1996“…The objective of this study was to solve the robot dynamic hybrid control problem using intelligent computational processes. In the course of problem- solving, biologically inspired models were used. …”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study
Published 2024“…Purpose/Objectives: Admission into dental school involves selecting applicants for successful completion of the course. This study aimed to predict the academic performance of Kulliyyah of Dentistry, International Islamic University Malaysia pre-clinical dental students based on admission results using artificial intelligence machine learning (ML) models, and Pearson correlation coefficient (PCC). …”
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
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Hybrid Metaheuristic Algorithm and Metaheuristic Performance Measurement for Solving University Course Timetabling Problem
Published 2007“…Metaheuristics have received considerable interest in the fields of applied artificial intelligence and combinatorial optimization such as university course timetabling problem (UCTP). …”
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Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph
Published 2023“…The course was divided into two groups, an experimental group and a control group. …”
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Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features
Published 2024journal::journal article -
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Intelligent traffic lights using Q-learning
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Proceeding Paper -
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Complementary K-Means clustering grouped the data into two major clusters, indicating that a clear differentiation between economic-based and entrepreneurship-based courses in terms of student enrolment volume and approval distribution. …”
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…The paper describes the development of intelligent chatbots that had been built for Java programming course. …”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Handbook of Machine Learning for Computational Optimization: Applications and Case Studies
Published 2021“…Individuals looking for machine learning-based knowledge will find interest in this handbook. …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach
Published 2024journal::journal article
