Search Results - (( wave optimization means algorithm ) OR ( wave optimisation based algorithm ))

Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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RFID data reliability optimiser based on two dimensions bloom filter by Yaacob, Siti Salwani, Mahdin, Hairulnizam, Kasim, Shahreen

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An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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A smart handover strategy for 5G mmWave dual connectivity networks by Abdullah, Nor Fadzilah, Gannapathy, Vigneswara Rao, Nordin, Rosdiadee, Abu-Samah, Asma

“…The developed algorithm underwent testing using a 5G mmWave statistical channel model that emulates a dynamic channel matrix, including fading and the Doppler effect. …”
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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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Interferometric array planning using division algorithm for radio astronomy applications by Kiehbadroudinezhad, Shahideh

“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey by Ukasyah Mahamod, Ibraheem Shayea, Hafizal Mohamad, Marinah Othman, Fauzun Abdullah Asuhaimi

Hydraulic characterization of PVC-O pipes by means of transient tests by Ghazali, M. F., Nizwan, Che Ku Eddy, Ismail, Nurazima, Sani, M. S.M., Yusof, Mohd Fadhlan M., Mohamed, Zamri

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Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Optimization of flood inundation simulation using multi-resolution Digital elevation model by Abdul Kadir, Muhammad Azraie

“…This is due to the limitation of diffusive wave algorithm, 2-dimensional model and effect of grid configuration. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Triple nonlinear hyperbolic PID with static friction compensation for precise positioning of a servo pneumatic actuator by Abdullah, Lokman, Kamaludin, Khairun Najmi, Syed Salim, Syed Najib, Rafan, Nur Aidawaty, Jamaludin, Zamberi, Rahmat, Mohd Fua'ad, Ramanathan, Rprakash

“…Although the FSS model caters to friction compensation, optimizing the FSS parameter by applying artificial intelligence, such as Neural Networks (NN) and Genetic Algorithm (GA), will increase the friction modeling‘s accuracy, and improve the compensation…”
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Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

“…The Malaysian Ageing and Retirement Survey (MARS) Data Wave 1 is used for this study where the data was sampled via multiple-stage sampling framework where each region is stratified by urban and rural areas called enumeration blocks (EBs) which are proportionate to the population size of each region across 3,384 households. …”
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