Search Results - (( normal distribution methods algorithm ) OR ( using optimization method algorithm ))*
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1
Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation
Published 2019“…The overall protection coordination is thus very complicated and could not be satisfied using the conventional method moreover for the modern distribution system. …”
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2
Optimal placement and sizing of distributed generation in radial distribution networks using particle swarm optimization and forward backward sweep method
Published 2012“…The proposed PSO algorithm is used to determine optimal placement and size of DG in radial distribution networks, where Forward Backward Sweep Method (FBSM) of distribution load flow analysis was used, to determine the actual power loss in the system. …”
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3
Profit-based optimal generation scheduling of a microgrid
Published 2023“…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”
Conference paper -
4
Protection Coordination Toward Optimal Network Reconfiguration and DG Sizing
Published 2019“…Constraints on protection coordination and DG size are explicitly formulated in the proposed method. The validity of the proposed method is analyzed on three commonly used IEEE 33-bus, 69-bus and 118-bus distribution systems, employing the firefly algorithm (FA) and evolutionary programming (EP) algorithm. …”
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5
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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6
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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7
Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
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8
Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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9
Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e
Published 2016“…The IEEE 802.11e standard aims to provide enhancements that allow traffic with specific requirements to be treated differently from normal traffic. Enhanced Distributed Channel Access (EDCA) is a fundamental and mandatory contention-based channel access method of IEEE 802.11e which delivers traffic based on differentiated Access Category (ACs). …”
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10
Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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11
PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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12
Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…In order to validate the models several cases are generated and demonstrated by two methods, Lingo 12.0 optimization software and an enumeration algorithm which is developed in C/C++. …”
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13
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Book Section -
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong
Published 2014“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. …”
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15
Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer
Published 2024“…The proposed strategy reduced the system’s total net present cost, power loss, and emissions by (1.06), (8.69), and (17.19), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. …”
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Bi-objective mixed integer nonlinear programming model for low carbon location-inventory-routing problem with time windows and customer satisfaction
Published 2024“…The IMNSGA-II produces the Pareto optimal solution set, and an entropy–TOPSIS method is used to generate an objective ranking of the solution set for decision-makers. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…One common method to obtain the true resistivity distribution is by inverting the apparent resistivity values. …”
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18
Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms
Published 2022“…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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Proceedings -
20
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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