Search Results - intelligence _ (drops OR cross) algorithm

Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm by AlDeeb, BA, Norwawi, NM, Al-Betar, MA, Jali, MZ

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Intelligent examination timetabling system using hybrid intelligent water drops algorithm by AlDeeb, Bashar A., Md Norwawi, Norita, Al-Betar, Mohammed A., Jali, Mohd Z.

“…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

Subjects: “…Intelligent water drops algorithm…”

Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

“…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

Subjects: “…Examination Time table, Intelligent Water Drops algorithm, Metaheuristic, Locale search algorithm, Optimization…”

Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm by Aldeeb, BA, Norwawi, NM, Al-Betar, MA, Bin Jali, MZ

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IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…This thesis presents an investigation of using the Intelligent Water Drops (IWD) algorithm to construct and produce good quality solutions for the UETP. …”

Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

“…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

“…Complex networks; Drops; Forecasting; Iterative methods; Network architecture; Network layers; Optimization; Rivers; Stochastic models; Stochastic systems; Stream flow; Time series; Engineering applications; Gradient-decent algorithm; Intelligent Water Drops (IWD); Multi layer perceptron; Multi-layer perceptron neural networks; Optimization algorithms; Streamflow forecasting; Time series prediction; Multilayer neural networks…”

Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology by Zhang, Hongli, Leong, Wai Yie

“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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Inverse modeling of mass transferprocess in the RDC column by fuzzy approach by Maan, Normah, Talib, J., Arshad, K. A., Ahmad, T.

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A new Doppler Spread Estimation Algorithm Based on Zero Crossings of The Auto-correlation by Altag Ali, Gassan, Jeoti , Varun, Manzoor, Shahid

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Enhanced Community Detection Based On Cross Time For Higher Visibility In Supply Chain: A Six-Steps Model Framework by Abal Abas, Zuraida, Mohd Zaki, Nurul Hafizah, Asmai, Siti Azirah, Abdul Rahman, Ahmad Fadzli Nizam, Zainal Abidin, Zaheera

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Genetic algorithm application for traffic light control by Turky A.M., Ahmad M.S., Yusoff M.Z.M., Sabar N.R.

“…In this paper, we describe the design of an intelligent traffic light control based on genetic algorithm. …”

A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network by Tee Y.K., Tiong S.K., Johnny K.S.P., Yeoh E.C.

Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…A few comparative results in downlink have shown that our integrated support vector regression assists genetic algorithm (SVRaGA) is capable of predicting next interval power consumption at Node B with low prediction error and improving the quality of service (QoS) by reducing dropped calls. � 2008 IEICE.…”

Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone by Md Jamal, Norezmi

“…With SNR of -5 dB, an improvement of 4% over DNN algorithm, 36% over conventional HRNR algorithm, and 12% over Log-MMSE algorithm are obtained. …”
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