hybrid evolutionary search method
Sidelobe-Level Suppression for Circular Antenna Array via New Hybrid Optimization Algorithm Based on Antlion and Grasshopper Optimization Algorithms
... and evolutionary algorithms, to guarantee integration in the new proposed ...an evolutionary algorithm in exploiting the global optimal solution along with balanced exploration of the search space, ...
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A hybrid modern and classical algorithm for Indonesian electricity demand forecasting
... The hybrid genetic algorithm (modern) and local search (classical) is an example of hybrid method that can offer an opportunity to find a global optimum solution for electrical energy demand ...
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Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm
... novel hybrid GA (HGA), which incorporates the local search method into GA, is proposed to be as an effective heuristic approach for the two-dimensional Euclidean ...local search crossover ...
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Proposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
... Cost-sensitive learning algorithms associate high misclassification costs for minority instances which misguide the search towards the minority class. If the cost associated with minority instances is too high, or ...
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Multiple-Constraint Synthesis of Rotationally Symmetric Sparse Circular Arrays Using a Hybrid Algorithm
... and evolutionary algorithms. In [14] and [15], the vector mapping (VM) method and matrix mapping method were used to handle complicated constraints for linear and planar arrays, ...total ...
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A Hybrid Predator Prey Optimization Method for the Design of Low Pass Digital FIR Filter
... using hybrid predator prey optimization (HPPO) ...an evolutionary algorithm that exhibits the features of basic PPO, hooke - jeeves exploratory move and opposition based strategy that helps to design an ...
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The Gradient Free Directed Search Method as Local Search within Multi-objective Evolutionary Algorithms
... Since we have chosen MOEA/D as base MOEA, it seems reasonable to test over the CEC09 benchmark [27]. For this, we adapted the available code from a specific version of MOEA/D [25], which was tested for performance with ...
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A Hybrid Optimization Technique Coupling an Evolutionary and a Local Search Algorithm for Economic Emission Load Dispatch Problem
... a hybrid multiobjective approach is pro- posed, which based on concept of co-evolution and re- pair algorithm for handing ...LS method was introduced as neigh- borhood search engine where it intends ...
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1. A frgsnn hybrid feature selection combining frgs filter and gsnn wrapper
... a hybrid model (FRGSNN) for data reduction combining fuzzy rough (FR) sets and an evolutionary genetic search algorithm (GS) is ...wrapper search(GS-NN) uses the machine learning algorithm ...
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Penguins Search Optimisation Algorithm for Association Rules Mining
... a hybrid method is used to reduce the cost, as well as to improve the original ...novel hybrid genetic based algorithm called PQGMA has been applied for association rules mining with the use of ...
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Meta Learning for Graph Neural Networks
... Deep Learning has provided breakthrough research results in many fields. Deep learning network’s ability to extract its own features for classification has provided it an edge over other machine learning techniques. It ...
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INFORMATION TECHNOLOGY GOVERNANCE USING COBIT 4 0 DOMAIN DELIVERY SUPPORT AND MONITORING EVALUATION
... Gravitational Search Algorithm (GSA) required to specify the crossover of our hybrid metaheuristic are presented in Section ...Movement Search Operator Phase (DMSOP) where a solution is modified ...
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Computational Complexity Measures for Many-objective Optimization Problems
... Single objective optimization problems, generally speaking, are intractable time-wise but have finite space (memory) requirements. Multi-objective optimization problems, on the other hand, are intractable both with ...
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Design of Genetic Fuzzy Based Diagnostic System to identify Chikungunya
... generating accurate and rapid diagnosis of disease. Particularly, in today’s era, there are several diseases whose symptoms are quite similar in initial stage. But at the same time, initial level diagnosis is also ...
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Online Full Text
... solution search block based on evolutionary algorithms and a decision making module based on a simulator of the ...of search technique) to a design process is very high due to the need to adequately ...
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Solving shortest path problem using gravitational search algorithm and neural networks
... The report for this study consists of four chapters. Chapter 1 presents an introduction to the study, problem background, objective, scope and significance of this study. Chapter 2 reviews the Shortest Path Problem Types ...
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AI Neural Network Disaster Recovery Cloud Operations Systems
... a mutation, the number of elements is calculated If , The mutation is not executed. The values of network mutation parameters used table 1 for the initialization of the weights of the networks, weights should be chosen ...
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Evolutionary neural architecture search for deep learning
... methods, evolutionary algorithms (EA) are especially suited for architecture search, where no gradient information with respect to the network structure is ...methods, evolutionary methods [118, 119] ...
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EVOLUTIONARY ALGORITHM: A CLASSICAL SEARCH AND OPTIMIZATION TECHNIQUE
... stochastic search algorithm. It is a subset of Evolutionary computation which is a generic population based metaheuristic optimization algorithm ...(partial search algorithm) that may provide a ...
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Plot Induction and Evolutionary Search for Story Generation
... Evaluation We compared the stories gener- ated by the GA against those produced by the rank-based system described in McIntyre and La- pata (2009) and a system that creates stories from the plot graph, without any ...
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