Search Results - (( simulation optimization method algorithm ) OR ( program segmentation matching algorithm ))
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1
Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…DSF algorithm is a hybrid stereo matching algorithm which divided into two phases. …”
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2
Word segmentation of output response for sign language devices
Published 2020“…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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3
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 -
4
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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5
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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6
Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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7
Improved particle swarm optimization by fast annealing algorithm
Published 2019“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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Proceeding Paper -
8
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 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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10
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
11
Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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Monograph -
12
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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Conference or Workshop Item -
13
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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14
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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15
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. …”
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Proceeding Paper -
16
Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images
Published 2018“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Thesis -
17
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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