Search Results - (( model evaluation means algorithm ) OR ( based observational based algorithm ))*

Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri by Ahmad Sukri, Nur Afiqah

“…The performance of the model is evaluated using metrics such as mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), precision, recall, F1-score, and accuracy. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…Recognition software achieved 87.14%, EPD algorithm achieved 73.57% and HMT algorithm achieved 74.30%) prediction accuracy with OTs. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Thirty trials have been performed to evaluate the SED, norm limited SPSA (NL-SPSA), global norm limited SPSA (G-NL-SPSA), and RS algorithms in each example. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Thirty trials have been performed to evaluate the SED, norm limited SPSA (NL-SPSA), global norm limited SPSA (G-NL-SPSA), and RS algorithms in each example. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Model performance, prioritising F1-score for MAEs, was evaluated using various measures. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Forecasting export of selected timber products from Peninsular Malaysia using time series analysis by Emang, Diana

“…The remaining ten quarterly observations (validation data set or out-of-sample data)were used to assess the forecasting abilities based on the measures of accuracy including mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). …”
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

“…The standalone and hybrid models have been tested to evaluate their performance via 5 metrics performances; (Coefficient of Determination (R2), Normalized Root Mean Square Error (NRMSE), Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE)), and Modified Taylor Diagram. …”

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm by Ehteram M., Panahi F., Ahmed A.N., Huang Y.F., Kumar P., Elshafie A.

Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

“…A reduction in the total number of features results in a less complex model. Based on the general observation, the nearest integer-based binary bat algorithm successfully optimized the selection of significant features due to recursive and repetitive searchability, in addition to its adaptive element in response to the current best solution in guiding the search process towards optimality. � 2022, Institute of Advanced Engineering and Science. …”

Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

“…Seven statistical indices have been selected to evaluate the performance of the proposed models. The selected statistical indices are root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), correlation coefficient (R), and coefficient of determination (R2), Nash Sutcliffe Model Efficiency Coefficient (NSE), and the RMSE-observations standard deviation ratio (RSR). …”

Artificial neural network technique for modeling of groundwater level in Langat Basin, Malaysia by Mahmoud Khaki, Ismail Yusoff, Nur Islami, Nur Hayati Hussin

“…The results indicated that the ANN technique was well suited for forecasting groundwater levels. All models developed had shown acceptable results. Based on the observation, the feed-forward neural network model optimized with the Levenberg-Marquardt algorithms showed the most beneficial results with the minimum MSE value of (0.048) and maximum R value of (0.839), obtained for simulation of groundwater levels. …”
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DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS by Lai, Wai Yan, Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman

“…Model performance was evaluated using the correlation coefficient and mean absolute error. …”
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RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING by MERDEKA, MOHAMMAD GALANG

“…The developed models were evaluated based on the fitting performance from adjusted R-square (????????????????…”
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Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro-climatic studies by Lawal, I.M., Bertram, D., White, C.J., Kutty, S.R.M., Hassan, I., Jagaba, A.H.

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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…The results obtained from the proposed meta-heuristic algorithms of this study were then evaluated for reservoir risk analysis, for the observed period assessment and the climate assessment. …”
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Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch by Fadilah, Norasyikin

“…Current harvesting methods based on observing the number of loose fruits on ground and the color of the fruits using human vision lead to subjective evaluation, laborious work, and low quality oil. …”
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