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检索条件"主题词=Crow Search Algorithm"

共 278 条记录，以下是81-90 订阅

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Multiple DG Allocation by crow search algorithm for Power Loss Reduction

Multiple DG Allocation by Crow Search Algorithm for Power Lo...

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IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (IEEE ICPCSI)

作者： NageswaraRao, M. Sumathi, N. Chaitanya, V. S. N. K. Amarendranath, K. JNTUK UCEK EEE Dept Kakinada India

ISBN: (纸本)9781538608142

This paper proposes a new meta-heuristic method for optimal sizing of distributed generator (DG). The objective of this paper is to reduce power losses and to improve voltage profile of the radial distribution network by placing multiple distributed generators at optimal locations. Analytical expressions are used in solving this paper for setting up of DG. In this study, crow search algorithm (CSA) is used for optimal sizing of distributed generators (DG). CSA is a meta-heuristic algorithm inspired by the intelligent behavior of the crows. crows stores their excess food in different locations and memorizes those locations to retrieve it when it is needed. They follow each other to do thievery to obtain better food source. This analysis is tested on IEEE 33 bus and IEEE 69 bus under MATLAB environment and the results are compared with the results of Improved analytical (IA) method and identified that percentage loss reduction in crow search algorithm is more than the percentage loss reduction in improved analytical method.

关键词： Distributed generation Optimal location Optimal DG size crow search algorithm IA method

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Detection of Dementia from Brain Tissues Variation in MR Images Using Minimum Cross-Entropy Based crow search algorithm and Structure Tensor Features 8th

Detection of Dementia from Brain Tissues Variation in MR Ima...

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8th International Conference on Soft Computing for Problem Solving (SocProS)

作者： Priyanka, N. Ahana Kavitha, G. Madras Inst Technol Dept Elect Engn Chennai 600044 Tamil Nadu India

ISBN: (纸本)9789811500350;9789811500343

Dementia causes cognitive dysfunction and deterioration of brain. Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) are most common forms of dementia. Globally, it is estimated that about 47 million people are affected by dementia. Various researches suggest that AD and MCI share a number of equally severe cognitive deficits, but the pathophysiology has not yet been addressed in a comprehensive way. An attempt is made to observe the prognosis difference in these disorders and to analyze the tissue variation in T1-weighted MR brain images. Samples used in this analysis are obtained from IXI, MIRIAD, and ADNI 2 database. Initially, skull stripping is carried out using Robust Brain Extraction Tool (ROBEX), Brain Extraction Tool (BET), and Brain Surface Extractor (BSE). Further, segmentation of brain tissues is performed using multilevel minimum cross-entropy based Bacteria Foraging algorithm (BFO) and crow search algorithm (CSA). Various geometric features and Structure Tensor (ST) features are extracted from White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF) for normal, MCI, and AD to observe the structural changes. The result shows that ROBEX performs better delineation of brain. Minimum cross-entropy based CSA achieves better segmentation than BFO based on similarity measures and computation time. Further, ST features extracted from the brain tissues are able to show anatomical variation effectively than geometric features. It is identified from the ANOVA test that structure tensor features of GM shows better variation to discriminate normal, MCI, and AD images. Hence, this framework could be used to differentiate normal, MCI, and AD images such as cognitive disorders effectively.

关键词： Dementia Bacteria foraging algorithm crow search algorithm Structure tensor

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Performance Evaluation of crow search algorithm on Capacitated Vehicle Routing Problem 1

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2nd International Conference on Soft Computing Systems (ICSCS)

作者： Dhanya, K. M. Kanmani, S. Pondicherry Engn Coll Dept Comp Sci & Engn Pondicherry India Pondicherry Engn Coll Dept Informat Technol Pondicherry India

ISBN: (数字)9789811319365

ISBN: (纸本)9789811319365;9789811319358

crow search algorithm is a novel Metaheuristic method based on the intelligent behavior of crows. It has been used to solve some optimization problems like engineering design problems, feature extraction and classification problems but has not been applied to vehicle routing problem. In this paper, crow search algorithm has been utilized to solve capacitated vehicle routing problem and the performance of it on various size-capacitated vehicle routing problem instances is analyzed. The factorial design ANOVA is used to determine the performance of crow search algorithm under different parameter settings on capacitated vehicle routing problem instances.

关键词： crow search algorithm Metaheuristic method Optimization problem Vehicle routing problem Capacitated vehicle routing problem Factorial design ANOVA

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Load Frequency Control of Security Constrained Deregulated Power System Using crow search algorithm 3

Load Frequency Control of Security Constrained Deregulated P...

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3rd International Conference for Convergence in Technology (I2CT)

作者： Pain, Santigopal Acharjee, Parimal Dr BC Roy Engn Coll Dept Appl Elect & Instrumentat Engn Durgapur India Natl Inst Technol Dept Elect Engn Durgapur India

ISBN: (纸本)9781538642733

In this paper, load frequency control (LFC) of nonlinear multi-area interconnected deregulated power system (DPS) is presented. To obtain realistic design, the DPS is modelled with reheat, non-reheat and hydro generators considering nonlinear security constraints - generation rate constraint (GRC), governor dead band (GDB), time delay (TD) and different system parameter values. A unique objective function is formulated by taking into account of the right combination of transient and steady state performance specifications with appropriate weighting coefficients. In this work, recently developed crow search algorithm (CSA) is used to obtain the optimal PID control gains for optimal steady state and transient performances. The performance of the proposed CSA based control system is compared with real codded GA (RGA) and enhanced PSO (EPSO) based control strategy. The proposed methodology gives best results in all cases.

关键词： crow search algorithm Deregulated power system LFC Security constraints

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A Novel MPPT Method Based on crow search algorithm Combined with Perturb & Observe for Partial Shading Conditions 12

A Novel MPPT Method Based on Crow Search Algorithm Combined ...

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12th IEEE Energy Conversion Congress and Exposition-Asia (ECCE-Asia)

作者： Tomar, Yashasvi Lian, K. L. Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan

ISBN: (纸本)9781728163444

Due to clouds, buildings, trees or any other blocking object, the shaded modules of the photovoltaic (PV) array receives less solar irradiation compared to unshaded modules. This causes occurrence of multiple peaks in the power-voltage characteristic curves (P-VCC). In this paper, we proposed a new MPPT method by combining crow search algorithm (CSA) and Perturb and Observe method to reduce the tracking time and increases tracking efficiencies. Experimental results show that the proposed method can drastically decrease the tracking time by more than 50%, while the tracking accuracy is also better, as compared to those of CSA.

关键词： crow search algorithm Maximum Power Point Tracking Perturb & Observe algorithm Partial Shading

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Bridges Reinforcement Through Conversion of Tied-Arch Using crow search algorithm 19th

Bridges Reinforcement Through Conversion of Tied-Arch Using ...

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19th International Conference on Computational Science and Its Applications (ICCSA)

作者： Valdivia, Sergio Crawford, Broderick Soto, Ricardo Lemus-Romani, Jose Astorga, Gino Misra, Sanjay Salas-Fernandez, Agustin Rubio, Jose-Miguel Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Valparaiso Valparaiso Chile Covenant Univ Ota Nigeria Univ Tecnol Chile INACAP Santiago Chile

ISBN: (纸本)9783030243081

The bridges reinforcement is an expensive activity. In this line, new cheap ways to fix bridges have been developed. One of them is the bridges reinforcement through conversion of the cable-stayed arch. The main aim is minimizing the distances between the tensions of each lengthwise position between the original bridge and the bridge with the reinforcement by the cable-stayed arch. For that, it is necessary to know the order that the tension must be applied. In this paper, we resolve this problem by using a recent metaheuristic called crow search algorithm which is based on the intelligent behavior of crows, this approach is inspired by the feature of crows to hide their excess food. The obtained results are compared other approximate techniques by using a well-known statistical test. Promising results reveal that this new algorithm is competitive to solve the proposed problem.

关键词： crow search algorithm Metaheuristic optimization Bridges reinforcement

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Distributed Energy Optimization Protocol using crow search algorithm in Underwater Acoustic Sensor Network for Energy Enhancement Comparing with Depth Based Routing algorithm 14

Distributed Energy Optimization Protocol using Crow Search A...

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14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)

作者： Reddy, K. Narasimha Ayyadurai, M. Saveetha Sch Engn Dept Elect & Commun Engn Chennai Tamil Nadu India

ISBN: (纸本)9781665460712

By combining a distributed energy optimization protocol and the crow search algorithm,An underwater acoustic sensor network's sensor nodes can be made to use less energy. ( DEOC SA) in contrast to the DBR protocol for depth-based routing. The Underwater Acoustic Sensor Network (UWASN) uses a 3D geographic zone for cooperative sampling to gather data and uses the crow search algorithm to distribute the data among the nodes.20 samples from each group were collected with a pre-test power of 80%, an error of 0.05, a confidence level of 95%, and 0.05 was chosen as the cutoff point for training the data sets. By changing the node distance, the proposed algorithm routing metrics are examined in a virtual underwater environment using the Aquasim patch and NS2 *** compared to DBR's energy (1mJ) with delay, the proposed DEOCSA performs best for dynamically changing environmental and geographical topological conditions (850ms) The statistical research demonstrates that the least significant value (P0.05) for energy optimization is energy (P=0.05).The simulation results show that by using the recommended crow search algorithm rather than Depth Based Routing algorithm, the sensor network's energy efficiency is increased by shortening the time spent choosing the best nodes.

关键词： UWASN crow search algorithm Depth-based Routing Energy Optimization Green Energy Artificial Intelligence Innovation

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A V-Shaped Binary crow search algorithm for Feature Selection

A V-Shaped Binary Crow Search Algorithm for Feature Selectio...

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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Thom de Souza, Rodrigo Clemente de Macedo, Camila Andrade Coelho, Leandro dos Santos Pierezan, Juliano Univ Fed Parana Adv Campus Jandaia do Sul Jandaia Do Sul Parana Brazil Pontificia Univ Catolica Parana Ind & Syst Engn Grad Program Curitiba Parana Brazil Univ Fed Parana Elect Engn Grad Program Curitiba Parana Brazil

ISBN: (纸本)9781509060177

Feature Selection (FS) is the process of identifying and separating relevant features of a dataset to obtain the best solutions for a pattern-classification or regression problem. The main benefits of FS include more accurate classification models, simplified interpretation of models and a reduction in the processing time required for classification. One of the main approaches used in FS involves wrappers. In this approach features are selected based on an evaluation performed by a classification algorithm. Recently, an optimization bio-inspired metaheuristic based on the intelligent behavior of crows called crow search algorithm (CSA) has been proposed. CSA works based on the idea that crows store their excess food in hiding places and retrieve it when the food is needed. The main reasons of using CSA are its easy implementation, few control parameters to adjust, fast convergence speed and high efficiency. To further enhance the performance of the classical CSA algorithm, this paper proposes a new wrapper based in a "vshaped" binarization of the CSA. The wrapper, which is referred to here as Binary CSA (BCSA), is applied to six benchmark data sets. The paper compares and discusses the advantages and disadvantages of the proposed technique in terms of classification accuracy, number of selected features and computational cost against some classical and state-of-art algorithms. The results were encouraging and showed that BCSA achieved very good results in terms of classification accuracy and also selected subsets with a small number of features with a relatively low computational cost.

关键词： feature selection classification wrapper crow search algorithm metaheuristics

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A Resource Aware VM Placement Strategy in Cloud Data Centers Based on crow search algorithm 4

A Resource Aware VM Placement Strategy in Cloud Data Centers...

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4th International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Satpathy, Anurag Addya, Sourav Kanti Turuk, Ashok Kumar Majhi, Banshidhar Sahoo, Gadadhar Birla Inst Technol Dept Comp Sci & Engn Mesra India Natl Inst Technol Dept Comp Sci & Engn Rourkela India

ISBN: (纸本)9781509045594

Virtual machine (VM) placement in cloud data centers is a challenging task. With the increasing popularity of cloud computing across the globe, a large number of VMs are to be consolidated on a minimum number of data centers (DCs) to optimize the energy consumption and data center utilization. In this paper, we propose a resource aware approach based on a metaheuristic crow search algorithm (CSA) to consolidate a large number of VMs on minimal DCs to meet the Service level agreement (SLA) and desired quality of service (QoS) with maximum data center utilization. We propose two independent techniques, (i) greedy crow search (GCS), (ii) travelling salesman problem based hybrid crow search (TSPCS), to meet the desired objectives. A comparative study has been made from the obtained results. To evaluate the performance of proposed methods we compare them with the classical First Fit (FF) approach and the proposed methods significantly outperform the classical method.

关键词： Virtual Machine Data Center Cloud Computing crow search algorithm Travelling Salesman Problem

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MOCSA: A Multi-Objective crow search algorithm for Multi-Objective Optimization 2

MOCSA: A Multi-Objective Crow Search Algorithm for Multi-Obj...

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2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)

作者： Nobahari, Hadi Bighashdel, Ariyan Sharif Univ Technol Dept Aerosp Engn Tehran Iran

ISBN: (纸本)9781509043309

In this paper, an extension of the recently developed crow search algorithm (CSA) to multi-objective optimization problems is presented. The proposed algorithm, called Multi-Objective crow search algorithm (MOCSA), defines the fitness function using a set of determined weight vectors, employing the max-min strategy. In order to improve the efficiency of the search space, the performance space is regionalized using specific control points. A new chasing operator is also employed in order to improve the convergence process. Numerical results show that MOCSA is closely comparable to well-known multi-objective algorithms.

关键词： crow search algorithm optimization weight vectors max-min strategy

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