Search Results - (( intelligence system drops algorithm ) OR ( intelligence 2 model algorithm ))

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…”

IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence by Singh, D.N., Murugamani, C., Kshirsagar, P.R., Tirth, V., Islam, S., Qaiyum, S., Suneela, B., Al Duhayyim, M., Waji, Y.A.

“…Artificial neural networks (ANNs) offer accurate technique modeling for complex systems using an artificial intelligence technique. …”
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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

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AI-enhanced generative design for efficient heat exchangers in thermoelectric generators: revolutionizing waste heat recovery in thermoelectricity / Andrew Robert Martin Hughes ...... by Andrew, Robert Martin Hughes, Bhathal Singh, Baljit Singh, Remeli, Muhammad Fairuz, Peixer, Guilherme Fidelis, Ratan Singh, Wandeep Kaur

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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

“…However, these methods are less effective when the non-linearity, complexity, and modeling uncertainties of the system increase. In recent years, a new discipline, known as artificial intelligence-based methods, has emerged, which allows the behavior of the system to be studied using operational data. …”
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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.

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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

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

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.

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

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

“…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”

Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context by Fakhar, Adila

“…The best configuration of the system is firstly selected by sensitively analyzing different microgrid models in terms of electricity price, initial capital cost, operating cost, carbon dioxide (CO2) emission reduction and the net present cost (NPC). …”
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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. …”

Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…This architecture is based on the combination of three well-known techniques, namely, artificial neural networks, fuzzy logic and genetic algorithm. The proposed architecture is implemented in the form of two models, namely, the neuro-fuzzy risk assessment model and the safe path selection model. …”

Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm by Tikhamarine Y., Souag-Gamane D., Najah Ahmed A., Kisi O., El-Shafie A.

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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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.

Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

“…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
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Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

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Development of intelligent 3D solid modeler based on artificial intelligent technique by Mohd. Zain, Azlan, Talib, Mohamad Shukor, Harun, Habibollah, Matondang, Muhammad Zaini, Mardzuki, Samihah

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