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

Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting by Abdulkadir, S.J., Yong, S.-P.

“…This paper presents an empirical long term chaotic financial forecasting approach using Parallel non-linear auto-regressive with exogenous input (P-NARX) network trained with Bayesian regulation algorithm. …”
Get full text
Get full text

Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia by Chuan, Zun Liang, Shao Jie, Ong, Yim Hin, Tham, Siti Nur Syamimi, Mat Zain, Yunalis Amani, Abdul Rashid, Ainur Naseiha, Kamarudin

“…The algorithm’s forecasting insights from the formulated algorithm could guide policymakers in establishing more effective regulations aligned with Sustainable Development Goals (SDGs) such as affordable and clean energy (SDG7), decent work and economic growth (SDG8), industry, innovation and infrastructure (SDG9), sustainable cities and communities (SDG11), responsible consumption and production (SDG12), and climate action (SDG13), which benefit economic, environmental, human, and social.…”
Get full text
Get full text
Get full text
Get full text

Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting by Afan H.A., Allawi M.F., El-Shafie A., Yaseen Z.M., Ahmed A.N., Malek M.A., Koting S.B., Salih S.Q., Mohtar W.H.M.W., Lai S.H., Sefelnasr A., Sherif M., El-Shafie A.

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

Get full text
Get full text
Get full text

A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
Get full text
Get full text
Get full text

Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

“…Multi-objective algorithm is proposed in this research which optimizes the ANN architecture that leads to enhancement in load forecast accuracy and reduction in the computational cost. …”
Get full text
Get full text

A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

“…This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. GDP forecasting is aided by the genetic algorithm radial basis neural network, which allows the government to make timely and effective macrocontrol plans based on the forecast trend of GDP in the region. …”
Get full text
Get full text

Forecasting The Financial Soundness Of Indonesia’s National Board Of Zakat (baznas) Using Artificial Neural Network Models by Syamsuri Syamsuri, Fuadah Johari, Nadhilah Nadhilah, Yaumi Sa’adah

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Real-world optimizations, such as forecasting streamflow, are a complicated process that is highly non-linear and multi-modal, demanding the use of a suitable modeling tool, with an emphasis on artificial intelligence algorithms, to get befitting forecast results. …”
Get full text
Get full text
Get full text

Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman by Abdurahman, Nur Athirah

“…The study focuses on the application of the Linear Regression algorithm to predict sales outcomes based on advertising spending patterns. …”
Get full text
Get full text

Load forecasting for air conditioning systems using linear regression and artificial neural networks by Zainudin, Zakaria Zikri, Yusoff, Siti Hajar, Gunawan, Teddy Surya, Mohamad, Sarah Yasmin, Chowdhury, Israth Jahan, Mohd Sapihie, Siti Nadiah

“…This study aims to develop a precise load forecasting model by integrating Linear Regression (LR) and Artificial Neural Networks (ANN). …”
Get full text
Get full text
Get full text
Get full text

Modelling particulate matter (PM10) concentration in industrialized area: A comparative study of linear and nonlinear algorithms by Abdullah S., Ismail M., Samat N.N.A., Ahmed A.N.

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. …”
Get full text
Get full text
Get full text

Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model by Salleh, Roselina, Shamsuddin, Siti Mariyam

“…Accordingly, the aim of this research is to develop a new hybrid model by combining a linear and nonlinear model for forecasting time series data. …”
Get full text
Get full text

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
Get full text
Get full text
Get full text

Rainfall time series modeling for a mountainous region in West Iran by Mekanik, Fatemeh

“…One of the major problems of water resources management is rainfall forecasting. Different linear and non-linear methods have been used in order to have an accurate forecast. …”
Get full text
Get full text

Hybrid OCSSA-VMD and optimized deep learning networks for runoff forecasting by Ma, Hong, Shareduwan Mohd Kasihmuddin, Mohd, Mansor, Mohd. Asyraf, Mohd Jamaludin, Siti Zulaikha, Marsani, Muhammad Fadhil, Che Rose, Farid Zamani

“…To improve accuracy and address the non-linearity and non-stationarity in monthly runoff forecasting, this paper proposes a method that integrates intelligent optimization techniques with Deep Learning (DL) network. …”
Get full text
Get full text
Get full text

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

“…Both internal and external features can influence a business's innovative development; thus, there must be relationships between these aspects for Innovative Development to succeed. …”
Get full text
Get full text

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.…”
Get full text
Get full text

Improving Time Series Models Prediction Based On Empirical Mode Decomposition Using Stock Market Data by Hossain, Mohammad Raquibul

“…Traditional forecasting methods have limitations in forecasting potentiality due to their linearity and stationarity assumptions on the datasets. …”
Get full text
Get full text