Search Results - (( location application a algorithm ) OR ( swarm optimization model algorithm ))

An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

“…Upon comparing with other optimisation algorithms, WOA and WOA-AIS displayed satisfactory performance in obtaining optimal BESS locations and sizing in distribution network. …”

Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…The basis of this compound is in such a way that the advantages of the Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) have been applied simultaneously. …”
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…A hybrid Particle Swarm Optimization-Bacterial Foraging Algorithm is developed for solving the single objective LIRP model. …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus of this paper is to find the optimal location of the collocated sensor-actuator and controller gains to actively control vibration, using a swarm intelligent algorithm called Ant Colony Optimization (ACO) and verified with Genetic Algorithm (GA). …”
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ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Impact of initialization of a modified particle swarm optimization on cooperative source searching by Ab. Majid, Mad Helmi, Arshad, Mohd Rizal, Yahya, Mohd Faid, Ibrahim, Abu Bakar

“…The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…Thereafter, the Multi-Leader Particle Swarm Optimization algorithm (MLPSO), which is a novel evolutionary optimization technique in the field of power systems was developed and employed in the optimization process. …”

Visual based SLAM using modified PSO by William, Low, Nagarajan, Ramachandran, Prof. Dr., Sazali, Yaacob, Prof. Dr.

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A survey on QoS requirements based on particle swarm optimization scheduling techniques for workflow scheduling in cloud computing by Ramadhan, Mazen Farid Ebrahim, Latip, Rohaya, Hussin, Masnida, Abdul Hamid, Nor Asilah Wati

“…This paper surveys scheduling algorithms based on particle swarm optimization (PSO). …”
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A variable-capacity-based fuzzy random facility location problem with VaR objective by Wang, Shuming, Watada, Junzo, Shamsul Bahar, Yaakob, Prof. Madya

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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

“…The current research is devoted to the implementation of hybrid novel meta-heuristic algorithms (e.g., the bat algorithm (BA) and particle swarm optimization (PSO) algorithm) to formulate multi-purpose systems for power production and irrigation supply. …”
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A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems by Yaseen Z.M., Ehteram M., Hossain M.S., Fai C.M., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., Hin L.S., Zaini N., Ahmed A.N., El-Shafie A.

Optimal Placement and Sizing of Distributed Generators Based on a Novel MPSI Index by Ruhaizad, Ishak, Azah, Mohamed, Abdalla, Ahmed N., Mohd Zamri, Che Wanik

“…The Objective: This paper presents a method to identify the optimal location and size of DGs based on the power stability index and particle swarm optimization (PSO) algorithm.Materials and methods: First, a novel maximum power stability index (MPSI) is derived from the well-established theorem of maximum power transfer. …”
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Comparative analysis of two-step GA-based PV array reconfiguration technique and other reconfiguration techniques by Muhammad Ajmal A., Ramachandaramurthy V.K., Naderipour A., Ekanayake J.B.

“…Dynamic models; Electric connectors; MATLAB; Particle swarm optimization (PSO); Photovoltaic cells; Software testing; Solar power generation; Comparative analysis; Comparative studies; Dynamic reconfiguration techniques; Dynamic techniques; Electrical connection; Matlab/Simulink software; Performance analysis; Real-time application; Genetic algorithms…”

Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania by Diaconu D.C., Costache R., Towfiqul Islam A.R.M., Pandey M., Pal S.C., Mishra A.P., Pande C.B.

“…It's worth noting that the application of the PSO algorithm significantly enhanced the model's performance. …”

Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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