Search Results - (( java implementation 5s algorithm ) OR ( program selection machine algorithm ))

Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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A hybrid intelligent algorithm for solving the bilevel programming models by Shamsul Bahar, Yaakob, Prof. Madya, Watada, Junzo

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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

Double-layered hybrid neural network approach for solving mixed integer quadratic bilevel problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

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A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

“…From the varieties of the machine learning algorithms, selecting the best model with the best configurations is a critical and complex design issue. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

Parallel computing via message passing: comparison between Microsoft MPI and Klyng framework / Nik Nasrul Faiz Nik Yahaya by Nik Yahaya, Nik Nasrul Faiz

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Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

“…In process planning of conventional milling, selecting reasonable milling parameters is necessary to satisfy requirements involving machining economics, quality and safety. …”
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Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

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DESIGN AND DEVELOPMENT OF HIGH-ACCURACY MACHINE FOR WIRE BENDING by Mustafa F.F., Hussein O., Fakhri O.F., Sabri A.H.

“…Firstly, using the proposed bending machine, in which the proposed algorithm is applied. …”

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”