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Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…The investigation is simulated using Intelligent Electricity Forecasting System (IEFS) developed in this research which written in Borland Delphi 7.0 programming.…”
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Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development by Kehinde, Okewu, Emmanuel, Okewu, Wong, Ling Shing, Siti Sarah, Maidin

“…The application of data engineering techniques like a genetic algorithm in forecasting outcomes in plant genetics and breeding can help solve the twin problems of food insecurity and insufficiency. …”
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Interactive control algorithm based on real-time solar irradiance forecasting model for standalone photovoltaic system by Mohd Shah, Ahmad Syahiman, Azri, Idris, Jadin, Mohd Shawal, Mohd Rashid, Muhammad Ikram, Mohd Saifizi, Saidon

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Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

“…Streamflow forecasting is paramount process in water and flood management, determination of river water flow potentials, environmental flow analysis, agricultural practices and hydro-power generation. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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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. …”
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Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems by Manu, Abdurrahman, Haja Mohideen, Ahmad Jazlan, Akhter, Muhammad Naveed, Ahmad Huzri, Muhammad Danial, Mohd Ibrahim, Azhar, Mohd Zaki, Hasan Firdaus, Sreeram, Victor

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Daily Rainfall Forecasting Using Meteorology Data with Long Short-Term Memory (LSTM) Network by Soo See, Chai, Goh, Kok Luong

“…Rainfall is a natural climatic phenomenon and prediction of its value is crucial for weather forecasting. For time series data forecasting, the Long Short-Term Memory (LSTM) network is shown to be superior as compared to other machine learning algorithms. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

“…Accordingly, two predictive models, namely, radial basis function neural network (RBF-NN) and support vector regression (SVR), have been developed to forecast monthly reservoir inflow. The test results revealed that the SVR forecasts monthly reservoir inflow better than the RBF-NN model. …”
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Appliance level stand-by burst forecast modelling using machine learning techniques by Mustafa, Abid

“…This work proposes a technique to model power consumption data and presents a comparative study of five different machine learning algorithms to study their suitability to forecast an appliance's state and standby burst. …”
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Dynamic forecasting model for short series age-specific mortality / Wan Zakiyatussariroh Wan Husin by Wan Husin, Wan Zakiyatussariroh

“…Hence, there is a need to develop and apply an appropriate model to produce good forecasts of Malaysia mortality. …”
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip by Mohd Taip, Muhammad Saifullah

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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R by Mohd Shamim, Nur Farisha Shuhada

“…Besides, this paper also enlightens on one of the Machine Learning tools used which is R, with the utilization of K Nearest Neighbor (KNN) algorithm as method of classification for data. This algorithm has been used to forecast on the end date of projects. …”
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Stock price monitoring system by Ng, Chun Ming

“…Algorithms trading is commonly practiced in the financial market due to high accuracy and least human error. …”
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Tourism Sustainable Competitiveness Indicator in Malaysia: Construct and Forecasting Ability by Ann Ni, Soh

“…The Multivariate Diebold-Mariano forecasting evaluation analysis was done to further evaluate and compare the forecasting ability of both TSCIs, before proceeding to the wavelet coherence analysis. …”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin by Che Wan Samsudin, Che Wan Sufia

“…In general, the condominium price prediction model developed using the Particle Swarm Optimization-Random Forest approach has high value for all real estate sector stakeholders, such as legal professionals, investors, and real estate developers, as it provides accurate price forecasts and practical insights.…”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

“…The development sequence of such method can be divided into two parts: Developing network structure to employ complex fuzzy logic and proposing learning algorithm to train the system. …”
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Predicting YSPSAH's product preferences across department of private hospitals by Abd Malik, Nur Aisyah Syahirah

“…Future enhancements could involve integrating real-time data and testing advanced forecasting algorithms to improve model performance. …”
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