Search Results - (( evolution optimization steam algorithm ) OR ( data interaction optimization algorithm ))
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1
Whale optimization algorithm strategies for higher interaction strength t-way testing
Published 2022“…To ensure that WOA conquers premature convergence and avoids local optima for large search spaces (owing to high-order interaction), three variants of WOA have been developed, namely Structurally Modified Whale Optimization Algorithm (SWOA), Tolerance Whale Optimization Algorithm (TWOA), and Tolerance Structurally Modified Whale Optimization Algorithm (TSWOA). …”
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2
Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network
Published 2017“…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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3
Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network
Published 2017“…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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4
A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
Published 2015“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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5
Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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6
A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
Published 2018“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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7
TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm
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8
VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. In proposed research work, the user is aided by a visualization based on the representation of multidimensional Genetic Algorithm data on 2-0 space. …”
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9
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. …”
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10
Heuristic task scheduling algorithms for optimal resource utilisation in grid computing
Published 2020“…This system usually handles workloads that are not interactive and include huge amount of data. The current challenge facing researchers is to determine the optimal task scheduling method that provides optimal resource utilisation in this extremely heterogeneous environment. …”
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A random search based effective algorithm for pairwise test data generation
Published 2011“…Pairwise (2-way or t = 2) interaction can find most of the software faults. This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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12
Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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13
Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization
Published 2022“…Considering multi-metric approaches and their implicit conflicting nature, it is necessary to handle this through effective multi-objective optimization algorithms. An effective optimization can be handled using a meta-heuristic approach with a high level of solution interactions. …”
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14
Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation
Published 2018“…Therefore, test data generation for t-way testing need to be optimized. …”
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15
Sizes of Superpixels and their Effect on Interactive Segmentation
Published 2021“…Despite the fact that it is used as a pre-processing step in many interactive segmentation algorithms, less studies had been conducted to assess the effects of the size of superpixels required by interactive segmentation algorithms to achieve an optimal result. …”
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Proceedings -
16
Sizes of Superpixels and their Effect on Interactive Segmentation
Published 2021“…Despite the fact that it is used as a pre-processing step in many interactive segmentation algorithms, less studies had been conducted to assess the effects of the size of superpixels required by interactive segmentation algorithms to achieve an optimal result. …”
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Proceeding -
17
T-way testing : a test case generator based on melody search algorithm
Published 2015“…Results shows that sometimes TTT-MS performed better than other existing strategies in certain data specification due to the behavior of optimization algorithms.…”
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Undergraduates Project Papers -
18
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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