Search Results - (( intelligence based costing algorithm ) OR ( intelligence based window algorithm ))

A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm by Adam, A.A., Soleimani, H., Shukur, M.F.B.A., Dennis, J.O., Abdulkadir, B.A., Hassan, Y.M., Yusuf, J.Y., Shamsuri, N.A.B.

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A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm by Adam, A.A., Soleimani, H., Shukur, M.F.B.A., Dennis, J.O., Abdulkadir, B.A., Hassan, Y.M., Yusuf, J.Y., Shamsuri, N.A.B.

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Predictive Analytics Of Cigs Solar Cell Using A Combinational Gra-Mlr-Ga Model by Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan, Mohd Zain, Anis Suhaila, Roslan, Ameer Farhan

“…Thin-film Copper Indium Gallium Selenide (CIGS) solar cell is identified to be one of the promising structures to replace conventional silicon-based solar cell due to its lower cost and reduced thickness. …”
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Implementation of an intelligent SINS navigator based on ANFIS by Ahjebory, Karim M., Ismaeel, Salam A., Alqaissi, Ahmed M.

“…As in previous work, which is based on Artificial Neural Network, the window based weight updating strategy was used, and the intelligent navigator evaluated using several SINS hypothetical field tests data. …”
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Network calculus-based latency for time-triggered traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN) by Shalghum, Khaled M., Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…The multi-objective-based algorithm, reinforcement learning algorithm, and different hybridizations are enhancing HFCEVs cost-competing edge. ? …”

RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review by YEJIAO, WANG, KAMALUDIN, HAZALILA, MOHAMMED ALDUAIS, NAYEF ABDULWAHAB, MOHD SAFAR, NOOR ZURAIDIN, ZHONGCHAO, HAO

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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

“…This study is aimed at proposing a superior artificial intelligence optimisation algorithm for sustainable river water quality management. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…The main problems which are faced by these fields include the high computational cost, memory cost, and low accuracy performance. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

“…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. Naïve Bayes is an intelligent method that depends on Bayes’ probability theory integrated with Adaptive Weight Ranking Policy (AWRP) via dynamic aging factor to improve the response time and network performance. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…Last system is based on the brushed DC motor. Objective function in this research, cost function was chosen. …”
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Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

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Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh D., Ismail F.B., Shakir Nasif M.

Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh, D., Ismail, F.B., Shakir Nasif, M.

“…The first intelligent warning system (IWS-1) represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2) represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. …”
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Intelligent biometric signature verification system incorporating neural network by Lim, Boon Han, Mailah, Musa

“…In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

“…The application of the recently developed flow direction algorithm, including its multi-objective variant with an �-based constraint-handling mechanism to OPF problem is the primary contributions of this work. …”

A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…In fact, current solutions in pipeline corrosion maintenance are extremely costly to the companies. The empirical solutions also lack intelligence in adapting to different environment. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…In fact, current solutions in pipeline corrosion maintenance are extremely costly to the companies. The empirical solutions also lack intelligence in adapting to different environment. …”
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