Search Results - (( new evaluation method algorithm ) OR ( risk optimization method algorithm ))
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1
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…The method adapts the original Non-Dominated Sorting Genetic Algorithm II (NSGA-II) by introducing a hybridisation of adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition techniques. …”
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7
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…The method adapts the original Non-Dominated Sorting Genetic Algorithm II (NSGA-II) by introducing a hybridisation of adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition techniques. …”
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8
AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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10
AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT
Published 2023“…Furthermore, this proposed method's optimality and fast convergence rate are satisfied.…”
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11
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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13
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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15
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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16
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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17
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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18
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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