Search Results - (( _ application new algorithm ) OR ( its ((relation based) OR (selection based)) algorithm ))*
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1
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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2
Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization
Published 2021“…This paper introduces a new variant of a metaheuristic algorithm based on Tiki-Taka algorithm, called selective chaotic maps Tiki-Taka algorithm (SCMTTA). …”
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Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat
Published 2019“…In addition, extraction rules including either pattern-based or dependency-based rules should be selected in a correct way to remove the irrelevant rules and minimize the extraction errors Thus, in this study, to select the most effective extraction rules, an improved version of Whale Optimization Algorithm (IWOA) is developed and applied to a full set of rules. …”
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6
Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Q-Learning’s reward function assigns the highest value to the least frequently executed action without taking into consideration its potential ability in detecting failures. Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…Q-Learning’s reward function assigns the highest value to the least frequently executed action without taking into consideration its potential ability in detecting failures. Furthermore, the proposed techniques based on the QLearning algorithm do not consider context-based actions. …”
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8
A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…Therefore, this paper presents a new mobile botnet classification based on permission and Application Programming Interface (API) calls in the smartphone. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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A fault syndromes simulator for random access memories
Published 2008“…The simulator allows a user through a GUI to select a March based test algorithm depending on the desired fault coverage and diagnostic resolution. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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An efficient fault syndromes simulator for SRAM memories
Published 2009“…The simulator allows a user through a GUI to select a March based test algorithm depending on the desired fault coverage and diagnostic resolution. …”
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13
Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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14
Multi-base number representation in application to scalar multiplication and pairing computation
Published 2011“…Multi-bases number representation is used to construct new versions of Miller’s algorithm. …”
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15
Comprehensive review of the development of the harmony search algorithm and its applications
Published 2019“…This paper presents a comprehensive overview of the development of the harmony search (HS) algorithm and its applications. HS is a well-known human-based meta-heuristic algorithm that mimics the process of creating a new harmony in music. …”
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Cluster head selection algorithm using fuzzy logic in multi-tier Wireless Sensor Network for energy efficiency / Wan Isni Sofiah Wan Din
Published 2016“…Hence, this study proposes a new algorithm called Multi-Tier Protocol (MAP). …”
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17
A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology
Published 2020“…The second stage relabels the consequent parts of multiple sets of k noisy fuzzy rules obtained from the first stage, such that a monotone fuzzy rule base is produced. The third stage selects the most suitable relabeled fuzzy rule base among the potential monotone fuzzy rule bases obtained from the second stage, either objectively or subjectively. …”
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…For optimal maintenance scheduling with low cost, high reliability, and low violation, the parameter values of the PACS algorithm were tuned using the Taguchi and Gray Relational Analysis (Taguchi-GRA) method through search-based approach. …”
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Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network
Published 2023“…Evaluated based on Mean Square Error (MSE) and Root Mean Square Error (RMSPE), the proposed BMO-ANN exhibits significant superiority over the other identified hybrid algorithms. …”
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A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links’ weight to increase network stability
Published 2014“…Thus, they decrease the weight accuracy in determining node’s competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node’s weight using its own features, but also considers the direct effect of feature of adjacent nodes. …”
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