Search Results - (( proposed solution learning algorithm ) OR ( java application based algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…Furthermore, the obtained results disclose the superiority of the proposed QOMJaya algorithm over both the proposed MJaya algorithm and several previous algorithms in terms of solution optimality and feasibility.…”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Additionally, an intelligent distributed cooperative power allocation learning algorithm is proposed to enhance energy efficiency in small cell networks while satisfying the scalability, power constraint, user association requirements, and QoS constraints. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…Two new adaptive routing algorithms named Enhanced Confidence-based Q (ECQ) and Enhanced Confidence-based Dual Reinforcement Q (ECDRQ) Routing Algorithms are proposed in this thesis. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

“…While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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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.

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. In this study, a benchmark dataset of energy consumption in a university campus of IIT, India (provided by the Smart Energy Informatics Lab, SEIL) was selected for training and testing the proposed variants of machine learning algorithms. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

“…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”

An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

“…The results reveal that the proposed algorithm outperforms non-interactive algorithms by providing superior solutions.…”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

“…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. In this research, we propose a new modified back propagation learning algorithm by introducing adaptive gain together with adaptive momentum and adaptive learning rate into weight update process. …”
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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

“…The second modification is the multiple population BH that is proposed as a generalization to the BH algorithm, in which the algorithm was not reliant upon the best solution but rather on a set of best solutions generated, called “MBH”. …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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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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