Search Results - ((((((research algorithm) OR (search algorithm))) OR (learning algorithm))) OR (new algorithm))

Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

“…Backpropagation; Gradient methods; Neural networks; Artificial neural network models; Complex applications; Exploration and exploitation; Gradient-based learning; Industry applications; Meta heuristic algorithm; Meta-heuristic search algorithms; Near-optimal solutions; Optimization…”

Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Modified Opposition Based Learning to Improve Harmony Search Variants Exploration by Al-Omoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

“…Harmony Search Algorithm (HS) is a well-known optimization algorithm with strong and robust exploitation process. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Nevertheless, many metaheuristic algorithms are still suffering from a low convergence rate because of the poor balance between exploration (i.e. roaming new potential search areas) and exploitation (i.e., exploiting the existing neighbors). …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…So,the selection of features is minimaland is not based on the previous learning process or what is known as heuristics. For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Trying through all the possible candidate clusters for the perfect result is too time consuming. Metaheuristic algorithm aims to search for global optimum in high dimensional problems. …”
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

“…In line with the no free lunch theorem (), this paper argues that rather than focusing on designing new algorithm, new research should focus on adaptive hybridization of meta-heuristics algorithms in order to compensate the limitation of one with the strengths of another. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Nevertheless, many meta-heuristic algorithms are still suffering from a low convergence rate because of the poor balance between exploration (i.e., roaming new potential search areas) and exploitation (i.e., exploiting the existing neighbors). …”
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The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

“…Thus, this research proposed a new method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL) which modifies the existing Back Propagation Gradient Descent algorithm by adaptively changing the gain, momentum coefficient and learning rate. …”
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Voltage stability index prediction by using genetics algorithm-based machine learning (GBML) technique / Zainab Mohd Ghazali by Mohd Ghazali, Zainab

“…The proposed technique is using Genetic Algorithms-Based Machine Learning (GBML) to predict the voltage stability index. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…From literature, Opposition-based Learning (OBL) has been employed to increase the diversity (exploration) of search algorithm by allowing current population to be compared with an opposite population. …”
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A conceptual model for the E-commerce application recommendation framework using exploratory search by Mohammed Mahmudur Rahman, Zulkifly Mohd Zaki, Md. Monirul Islam, Najwa Hayaati Mohd Alwi

Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…RBFN-DDA performs incremental learning wherein its structure expands by adding new hidden units to include new information. …”
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