Search Results - (( basic optimization based algorithm ) OR ( based optimization means algorithm ))
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Thesis -
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture
Published 2021“…The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. …”
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Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.]
Published 2016“…It is also find that due to full acces level, the self-made simulator as used in the research has good potential to be used in the optimization case with search algorithm.…”
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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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Noise Cancellation method in assistive listening system
Published 2020“…Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. …”
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Undergraduates Project Papers -
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…To achieve the task of a longer network lifetime and higher average node energy, we have proposed an energy-efficient routing protocol motivated from the concept of well-known Low Energy Adaptive Cluster Hierarchy routing algorithm also known as LEACH, and optimized it with the concept of alternate hitting, which means the even-odd scheduling-based routing. …”
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A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana
Published 2018“…Since the similarity of the two distributions is close, it means that the optimized corpus can perform as efficient as the larger corpus. …”
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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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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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SNR-Based OLSR Routing Protocol for Wireless Mesh Networks
Published 2009“…Unfortunately the routing protocols used such as AODV and Dynamic source routing (DSR) are hop count-based; where the routing algorithm uses the number of nodes to determine the optimum path to the destination. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024“…In this paper, a new ABC algorithm called MeanABC is introduced to achieve the search behavior balance via a modified search equation based on the information of the mean of the previous best solutions. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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Conference or Workshop Item -
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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