Search Results - (( new evaluation step algorithm ) OR ( whale optimization path algorithm ))
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2021“…To solve the redundancy resolution, meta-heuristic optimizations, namely Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA), are applied to search optimal trajectories inside local orientation angle boundaries. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Revolutionizing crowd safety: A breakthrough hybrid whale-bat chaotic algorithm (WOABCM) for optimized evacuation simulations
Published 2024“…The Whale-Bat Chaotic Algorithm (WOABCM) is a revolutionary tool for optimizing pathfinding navigation in crowd evacuation scenarios. …”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2018“…PSO is also compared with another algorithm like Whale Optimization Algorithm, Ant Lion Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Moth-flame Optimization and Sine Cosine Algorithm. …”
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Book Chapter -
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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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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs
Published 2023“…This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). …”
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Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH
Published 2018“…This study is proposing a new algorithm of Box-Jenkins and GARCH (or BJ-G) in evaluating the multistep forecasting performance of the BJ-G model for highly volatile time series data. …”
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Conference or Workshop Item -
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DC-link capacitor voltage control for single-phase shunt active power filter with step size error cancellation in self-charging algorithm
Published 2016“…This study presents an improved self-charging algorithm by introducing a new feature known as step size error cancellation for better performance of DC-link capacitor voltage control in single-phase shunt active power filter (SAPF). …”
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A new variable step size block backward differentiation formula for solving stiff initial value problems
Published 2013“…A new block backward differentiation formula of order 4 with variable step size is formulated. …”
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Solving ump examination timetabling problem using dynamic exploration step counting hill climbing algorithm
Published 2022“…Then, the initial solution is improved using our enhanced algorithm called dynamic exploration step counting hill climbing (DESCHC). …”
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Thesis -
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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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Thesis -
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DC-link capacitor voltage control for single-phase shunt active power filter with step size error cancellation in self-charging algorithm
Published 2016“…This study presents an improved self-charging algorithm by introducing a new feature known as step size error cancellation for better performance of DC-link capacitor voltage control in single-phase shunt active power filter (SAPF). …”
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