Search Results - (( global optimization method algorithm ) OR ( probable detection method algorithm ))
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Microcrack Detection And Noise Reduction In Integrated Circuit Packages
Published 2018“…Three algorithms are tested and evaluated in terms of microcrack detection and noise reduction which are probability based thresholding, histogram equalization, and modified Perona-Malik’s anisotropic diffusion methods. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems
Published 2018“…However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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A Comparison of Particle Swarm optimization and Global African Buffalo Optimization
Published 2020“…However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. …”
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Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems
Published 2017“…This study presents a hybrid invasive weed firefly optimization (HIWFO) algorithm for global optimization problems. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)
Published 2016“…Several global methods have been proposed for solving discrete optimization problems. …”
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An analysis of low complexity of 5G-MIMO communication system based CR using hybrid filter detection
Published 2022“…Thus, a 5G-MIMO based CR communication system has been developed to enhance the spectrum by employing a spectrum sensing (SS) algorithm. This recommended SS algorithm, based on the hybrid filter detection (HFD) method, employs the Cosine law for filtering the traffic signal, and then enables segmentation by applying the Welch algorithm. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS
Published 2014“…This paper focuses on optimality of analytical study on the common soft fusion (SDF) CSS based on different iterative algorithms which confirm low total probability of error and high probability of detection in details. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization
Published 2019“…In another hand, numerical results of ABCED Conjugate Gradient Methods also achieved up to 80.95% of the selected benchmark global optimization been solved successfully. …”
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Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance
Published 2016“…This paper focuses on optimality of analytical study on the common soft decision fusion (SDF) CSS based on different iterative algorithms which confirm low total probability of error and high probability of detection in detail. …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…There are several methods in two categories to solve MRO problems. The first category includes premier methods such as Response Surface Methodology (RSM) and Taguchi method and the second one includes newer methods like hybrid methods of ANNs and Genetic Algorithm (GA). …”
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