Search Results - (( evaluation forecasting linear algorithm ) OR ( java implication based algorithm ))

Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

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An artificial neural network hybrid with wavelet transform for short-term wind speed forecasting: A preliminary case study by Yousefi M., Hooshyar D., Yousefi M., Khaksar W., Sahari K.S.M., Alnaimi F.B.I.

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

“…Overall, this study advances the science of weather forecasting by showing how well ANN algorithms can capture intricate weather patterns.…”
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Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The other foremost contribution of the work is proposing a hybrid electricity price forecasting technique to provide more accurate forecasts. …”
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Analysis of short term load forecasting techniques / Tan Vy Luoh by Tan, Vy Luoh

“…In this report, three common numerical STLF techniques including Multiple Linear Regression (MLR), Curve Fitting and Bagged Tree Regression are proposed to forecast one-day ahead load profile with a yearly historical load data. …”
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Tourism Forecasting And Tackling Fluctuating Patterns : A Composite Leading Indicator Approach by Puah, Chin Hong, Soh, Ann Ni, Mohammad Affendy, Arip

“…A growing interest is surfacing toward the non-linearities in tourism demand forecasting. This paper aims to construct a tourism composite indicator to anticipate the cyclical movement for the tourism demand in Fiji. …”
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Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review by Mustafa H.M., Mustapha A., Hayder G., Salisu A.

Forecast innovative development level in green supply chains using a comprehensive fuzzy algorithm by Delgoshaei, Aidin, Beighizadeh, Razieh, Mohd Arffin, Mohd Khairol Anuar, Leman, Zulkiflle, Ali, Ahad

“…The suggested support vector machine model was also evaluated in 30 case studies, demonstrating that the model is capable of accurately forecasting technological advancement in green supply chains (score: 0.81). …”
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Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia by Ridwan W.M., Sapitang M., Aziz A., Kushiar K.F., Ahmed A.N., El-Shafie A.

Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Despite advances in deep learning, existing forecasting models often struggle with the complex temporal dependencies and non-linear patterns in chiller operation data. …”
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ARTIFICIAL NEURAL NETWORK FOR WATER LEVEL PREDICTION IN A RIVER UNDER TIDAL INFLUENCE by Maliana, Sa'ad

“…An Artificial Neural Network is undoubtedly a robust tool for forecasting various non-linear hydrologic processes, including the water level prediction. …”
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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…Additionally, pre-processing is conducted using the RapidMiner application prior to mapping the cleaned data with three distinct algorithms for predictive analysis: Decision Tree, Random Forest, and Multiple Linear Regression techniques. …”
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Modelling hourly runoff using ann for sg. Sarawak Kanan Basin by Chong, Kah Weng.

“…An Artificial Neural Network is undoubtedly a robust tool for forecasting various non-linear hydrologic processes, including develop a rainfall-runoff model. …”
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Hourly water level prediction of sungai bedup catchement using pre-developed ANNs model from Siniawan catchment by Hong,, Calvin Chiao Chun

“…An Artificial Neural Network is undoubtedly a robust tool for forecasting various non-linear hydrologic processes, including the water level prediction. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

Groundwater level prediction using machine learning algorithms in a drought-prone area by Pham Q.B., Kumar M., Di Nunno F., Elbeltagi A., Granata F., Islam A.R.M.T., Talukdar S., Nguyen X.C., Ahmed A.N., Anh D.T.