Search Results - (( edge detection swarm algorithm ) OR ( based optimization strategy algorithm ))*

Efficient edge detection using fuzzy heuristic particle swarm optimization / Noor Elaiza Abdul Khalid, Mazani Manaf and Mohd Ezane Aziz by Abdul Khalid, Noor Elaiza, Manaf, Mazani, Aziz, Mohd Ezane

“…In this research the PSO is used to optimize the edge detection detected by the CFH algorithm and it is referred to as FHPSO. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Semi-automatic cortical boundary detection / Noor Elaiza Abdul Khalid. by Abdul Khalid, Noor Elaiza

“…LPHA proves to be an efficient edge detector evaluation algorithm and FPSO is proven to be an effective edge detection algorithm.…”
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

“…First, proposed the Non-dominated Particle Swarm Optimization (NPSO) algorithm for workload allocation to reduce transmission delay in edge-cloud computing and imbalance load degree in edge-fog computing. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Particle swarm optimization based articulated human pose tracking using enhanced silhouette extraction by Saini, S., Rambli, D.R.B.A., Sulaiman, S.B., Zakaria, M.N.B., Tomi, A.B.

“…Both the silhouette and edge likelihood are used in the fitness function. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system by Nasir, Ahmad Nor Kasruddin, Abdul Razak, Ahmad Azwan

“…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

“…In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case which is an NP-Complete problem. This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. …”
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An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms by Alsewari, Abdulrahman A., Kamal Z., Zamli

“…This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm Optimization based strategy (PSTG), and Harmony Search Strategy (HSS). …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

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Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

“…For further assessment, the proposed design strategy is then employed to design a control law for an electrical DC drive velocity controller used as a benchmark problem for the recent PSO-based and genetic algorithm optimization (GAO)-based robust controllers. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Two main aspects are used to classify the evolutionary algorithm variants: population-based and evolutionary strategies (variation and replacement). …”
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Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing by Din, Fakhrud, Kamal Z., Zamli

“…Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

“…Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abdul Ghani, Mohammad Osman, Tokhi

“…The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. …”
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