Search Results - (( simulation optimization using algorithm ) OR ( ais implementation using algorithm ))
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1
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Thesis -
2
Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms
Published 2013“…In this paper, starting from the set of equations modeling a PV module, an innovative procedure to optimize the performance and efficiency of the MPPT algorithms is presented, simulated and verified. …”
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Final Year Project -
3
Null steering of adaptive beamforming using linear constraint minimum variance assisted by particle swarm optimization, dynamic mutated artificial immune system, and gravitational...
Published 2023“…Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program. © 2014 Soodabeh Darzi et al.…”
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Artificial neural controller synthesis for TORCS
Published 2015“…As a conclusion, this research has shown that the DE hybrid FFNN algorithm and PDE hybrid FFNN algorithm are useful and promising in evolving autonomous car racing controller.…”
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5
Image recognition using Artificial Immune systems approach
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Working Paper -
6
SNR estimation using extended kalman filter technique for orthogonal frequency division multiplexing (OFDM) system
Published 2012“…This is because in OFDM system, robustness in frequency selective channels can be achieved using adaptable transmission parameters. Therefore, to reckon these parameters, knowledge of SNR estimates obtained by channel state information is required for optimal performance. …”
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7
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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8
Social learning and principal-agent problems in profit sharing contract
Published 2023“…The data are collected from the period of 2009 to 2013 and it will be used for the simulation process by utilizing the genetic algorithm technique. …”
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Design optimization and navigation for autonomous guided vehicle (AGV) in agriculture plantation
Published 2024“…Some simulations and experiments have been successfully performed in a computer-based simulation and farm.…”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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11
Application of minimax algorithm in dots and boxes game
Published 2025“…The methodology involved implementing the Minimax algorithm as the primary decision-making engine for the AI. …”
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Final Year Project / Dissertation / Thesis -
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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13
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…However, these extensions may result in increased execution times for the algorithm. In this research, a new combinatorial algorithm named discrete simulated Kalman filter optimizer (DSKFO) is proposed to solve combinatorial optimization problem. …”
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14
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Conference or Workshop Item -
15
Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation
Published 2023“…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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Proceeding -
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Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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20
Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…The predictive part determines the feasible schedule to be used for a flow shop which is generated using a combination of rule-based simulation and optimization: first, using the optimization algorithm to compute a rough plan, followed by using a rule based simulation system to locally fine tune the plan to obtain the final schedule. …”
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