Search Results - (( evaluating forecasting practices algorithm ) OR ( java implication based algorithm ))

Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…In evaluating the performance of the multistep ahead forecast, the proposed algorithm is employed to daily world gold price series of 5-year data. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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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

“…In order to examine the accuracy of monthly water level forecasts, effectiveness of the steepness coefficient in the sigmoid function of a developed ANN model was evaluated in this research. …”
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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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A review and comparative analysis of predictive models for supply chain demand forecasting by Ibrahim Ahmed Omer, Rehab, Hassan, Raini, S. Abd. Aziz, Madihah

“…By synthesizing current research and implementation insights, this work provides a comprehensive evaluation of existing methods, identifying their strengths, limitations, and future research directions to enhance data-driven demand forecasting in modern supply chains.…”
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Leveraging artificial intelligence in modern supply chains by Ng, Qiao Ying

“…A Streamlit-based dashboard was designed to visualize model performance, predicted traffic conditions, optimized routes, and system-level evaluations in a simulated real-time environment. Evaluation results demonstrated that the LSTM model achieved reliable short-term forecasts, outperforming a baseline by more than 25% in error reduction, while the congestion-aware routing consistently avoided heavily congested edges. …”
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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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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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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. Thirdly, while undertaking a literature review to gain insights into current mortality forecasting models, it became apparent that a gap existed between the current models used for forecasting and projecting Malaysia mortality and the current practice of incorporating state-space methodology in mortality forecasting models, specifically in modelling high-dimensional short series mortality data. …”
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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

“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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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

“…This research contributes to the advancement of accurate and efficient chiller power consumption forecasting methodologies, offering practical implications for Heating, Ventilation, and Air Conditioning (HVAC) system optimization and energy efficiency improvements in commercial buildings.…”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

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

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Stock price monitoring system by Ng, Chun Ming

“…Consequently, Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the performance of the prediction algorithms. …”
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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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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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The prediction of stock management for Farmasi Chendering by Gamal, Nurul Fatihah

“…This project focuses on Farmasi Chendering, aiming to develop a predictive stock management system using ABC-VEN analysis and the J48 decision tree algorithm. The adapted CRISP-DM methodology guided the development process, encompassing data preparation, modeling, evaluation, and deployment. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

“…At present, most of the researches are theoretical in nature, and practical works are presented to apply complex fuzzy logic for signal processing and time-series forecasting where the system is univariate. …”
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

“…The experiments were carefully conducted at various time intervals, and the machine learning procedures used in this study were all employed to forecast catalytic performance. The evaluation of the performance of such algorithms were done by means of Mean Absolute Error. …”

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush