Search Results - (( developing agent function algorithm ) OR ( java evaluation model algorithm ))
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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Thesis -
2
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
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3
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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4
Factor Strategy Model: Proofs of Prototype Concept for Software Quality Evaluation
Published 2010“…The objective of this study is to provide software developers some measures to evaluate software quality of a Java program. Studies on software quality requirements, software quality models (as a quantifying measurement technique) and various good design rules are required for. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
6
Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…However, the evaluation function used in the AI is developed based on historical traffic data. …”
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7
Development of gene motif modulation for information processing in artificial DNA computing
Published 2014“…In the artificial DNA computing model, the MAS (Multi-Agent System) algorithm depicts the sender agent transmits moleware information through the control agent which is then converted to binary data as input to the receiver agent. …”
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Proceeding Paper -
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Development of a Negotiation Support Model for Value Management in Construction
Published 2009“…The research objectives are to find a theoretical basis and research approach for negotiation support methodology on VM, to develop a decision model for technical solution options in a satisfying function/cost preferences, to investigate negotiation style and outcome and analyze the correlation between them for the basis of scenarios on the agent system, to develop a model for agreement options and coalition algorithms on value-based decision, to validate the coalition algorithms and introduce an initial model of Negotiation Support for Value Management (NSVM). …”
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Final Year Project -
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). However, the process failed to state clearly the encoding strategy in its initial stage. …”
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11
Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning
Published 2022“…Fifth, a novel agent selection algorithm was developed to enable the selection of the best agent and avoid under-fitting and over-fitting. …”
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12
Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…Besides biology, physics and chemistry, state estimation algorithm also has become a source of inspiration for developing metaheuristic algorithms. …”
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Conference or Workshop Item -
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Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…Moreover, results indicate that agents equipped by this learning capability can generate Pareto-efficient offers by MGT algorithm. …”
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15
CSGO: a game-inspired metaheuristic algorithm for global optimization
Published 2023“…This paper presents a video game-inspired meta-heuristic algorithm and its performance evaluation. This optimizer algorithm is developed by assembling impressive features of previous well-known optimizer algorithms such as stochastic fractal search (SFS), artificial gorilla troops optimizer (GTO) and marine predators algorithm (MPA) with addition of chaotic operators. …”
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Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines
Published 2025“…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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Article -
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A modified crow search algorithm with niching technique for numerical optimization
Published 2019“…The search agent of the primitive crow search algorithm does not always follow the best solution obtained so far. …”
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A modified crow search algorithm with niching technique for numerical optimization
Published 2019“…The search agent of the primitive crow search algorithm does not always follow the best solution obtained so far. …”
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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
Published 2013“…In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. …”
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20
Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method
Published 2024“…The algorithms are assisted with penalty function method during the selection of new agents/ offsprings to confirm the generations that violated the constraints are superseded during the next generation selection. …”
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