Search Results - (( using evolutionary sensor algorithm ) OR ( basic evaluation method algorithm ))
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Existing approaches for this optimization problem have several drawbacks, including non-adaptive network configuration that may cause premature death of sensor nodes. Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Efficient transmission based on genetic evolutionary algorithm
Published 2022“…Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. …”
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Proceedings -
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Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
Published 2023“…Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage. © 2014 King Fahd University of Petroleum and Minerals.…”
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WSN sensor node placement approach based on multi-objective optimization
Published 2023“…A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. …”
Conference Paper -
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms
Published 2012“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Research Report -
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. …”
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Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks
Published 2013“…One of such is the difficulty in determining the most suitable learning algorithm for optimal model performance. To save the cost, effort and time involved in the use of trial-and-error and evolutionary methods, this paper presents an ensemble model of ANN that combines the diverse performances of seven "weak" learning algorithms to evolve an ensemble solution in the prediction of porosity and permeability of petroleum reservoirs. …”
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Proceeding -
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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Monograph -
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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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Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…Voltage stability margin (VSM) can be basically identified by the multi-solution load flow calculation method. …”
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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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Data depublication using : Hashing algorithm / Naimah Nayan
Published 2019“…The recommendation for future work is to evaluate various type of data and different type of hashing algorithm.…”
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An ensemble feature selection method to detect web spam
Published 2018“…Moreover, the best values of evaluation metrics in our proposed method are optimal in comparison to the other methods reported in this paper. …”
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