Search Results - (( data estimation using algorithm ) OR ( variable training based algorithm ))

SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…The proposed data store management technique is combined with the central finite difference based gradient estimate to generate a model robust against both correlated data and irregular sampled data. …”
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Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh by Saleh, Pauziah

“…The variable input data of armature voltage, armature current and output speed were collected by using simulation of the system. …”
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Design of Artificial Neural Network (ANN) based rotor speed estimator for DC drives / Siti Mutrikah Abd Mokhsin by Abd Mokhsin, Siti Mutrikah

“…For this purpose the Levenberg-Marquardt back-propagation algorithm was used. The training took only a few minutes on a PC and for this purpose 30000 inputoutput training data were used. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. Levenberg-Marquardt algorithm is used as the training algorithm. …”
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A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling by Purnomo, Muhammad Ridwan Andi, Abdul Wahab, Dzuraidah, Hassan, Azmi, Rahmat, Riza Atiq

“…PGA is included in the TSK-Fuzzy system to determine the optimum parameters in the Fuzzy sets and Fuzzy rules so as to improve the accuracy of the tire-road slippage index estimation. A set of data in a size of 38 × 4 and 22 × 4 were used for training and testing the performance of the model. …”
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Hybrid histogram and neural based call admission control for VBR video traffic. by Khalil, Ibrahim, Mohd Ali, Borhanuddin

“…We have shown how performance data derived from histogram based approach can be used as training data in the NN training scheme to produce even better results than the pure histogram based approach, while still retaining the merits of it.…”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

“…The ANN-based models could serve as reliable and useful tools in estimating the WQI of the river.…”
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Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

Air Pollution Index Estimation Model Based On Artificial Neural Network by Mohammed Nasser, Al-Subaie

“…Environmental conservation efforts are always dealing with a complex problem because it involves a large number of variables. However, choosing a correct model structure, and optimum training algorithm with minimum complexity is crucial. …”
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Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

“…The cross-validation is common technique used to prevent over fitting problem by dividing the data into two categories namely data training and data test. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Assessment of predictive models for chlorophyll-a concentration of a tropical lake. by Malek, S., Syed Ahmad, S. M., Singh, S. K., Milow, P., Salleh, A.

“…RESULTS: Same data set was used for models development and the data was divided into two sets; training and testing to avoid biasness in results. …”
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Assessment of predictive models for chlorophyll-a concentration of a tropical lake. by Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Malek, Sorayya, Kashmir Singh, Sarinder Kaur, Milow, Pozi, Salleh, Aishah

“…RESULTS: Same data set was used for models development and the data was divided into two sets; training and testing to avoid biasness in results. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…This article proposes an effective machine learning (ML) approach to achieve the optimal design of the charging track, considering the cross-coupling effect. The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”

Predicting Diseases Using Multi-BackPropagation by Wan Hussain, Wan Ishak

“…That is in the multi network approach all data sets are used in training. The knowledge (weight) produced by the network can be applied for all possible data sets. …”
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Comparison of estimation capabilities of the artificial neural network with the wavelet neural network in lipase-catalyzed synthesis of triethanolamine-based esterquats cationic su... by Masoumi, Hamid Reza Fard, Basri, Mahiran, Kassim, Anuar, Abdullah, Dzulkefly Kuang, Abdollahi, Yadollah, Abd Gani, Siti Salwa

“…After training of the artificial neurons in ANN and WNN, using the data of 30 experimental points, the products were used for estimation of the response of the 18 experimental points. …”
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