This study presents a novel forecasting framework that integrates Genetic Algorithms (GA) with Long Short-Term Memory (LSTM) networks to enhance the prediction accuracy of passenger volumes in Thailand's public transportation systems.
Khumla Pornsiri, Sarawan Kamthorn
doaj +1 more source
Accurate short-term prediction of residential power consumption is imperative for efficient energy system management. However, the complexity of high-resolution load data, nonlinear dynamics of load fluctuation, and external factor interactions pose ...
Yitao Zhao +3 more
doaj +1 more source
Machine learning models for performance estimation of solar still in a humid sub-tropical region
In the current investigation, machine learning models were developed to estimate the performance of a solar still in a humid subtropical climate region. A single-slope passive solar still was designed and constructed to facilitate year-round experiments ...
Farooque Azam +2 more
doaj +1 more source
Forecasting Inflation in Developing Economies: The Case of Nigeria, 1986-1998 [PDF]
In this article, we have sought to establish whether monetary aggregates have useful information for forecasting inflation, other than that provided by inflation itself. We have approached the problem in two ways.
Adebiyi, M.A., Feridun, M.
core
Transforming oil market analysis: A novel GAN + LSTM predictive framework
A novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari +2 more
doaj +1 more source
Oil and Product Price Dynamics in International Petroleum Markets [PDF]
In this paper we investigate crude oil and products price dynamics. We present a comparison among ten price series of crude oils and fourteen price series of petroleum products, considering four distinct market areas (Mediterranean, North Western Europe,
Alessandro Lanza +2 more
core
L'évaluation hors-ligne permet d'estimer la qualité d'un modèle prédictif à partir de données historiques. En pratique, cette approche estime la qualité d'un modèle avant sa mise en production, sans interagir avec les clients ou utilisateurs. Pour qu'une évaluation hors-ligne soit pertinente, il est nécessaire que les données utilisées soient sans ...
openaire +1 more source
Perbandingan Metode SAW dan AHP pada Sistem Pengambilan Keputusan Pemilihan Supplier Berbasis Web dengan Algoritma Regresi ANN dan SVM [PDF]
UD. Berkah Jaya is a cold storage company facing challenges in selecting the appropriate suppliers to meet its stock requirements. Decision Support Systems (DSS) methods such as Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP) are ...
Jamalludin, Jamalludin
core
Redefining multi-target weather forecasting with a novel deep learning model: Hierarchical temporal convolutional long short-term memory with attention (HTC-LSTM-Attn) in Bangladesh. [PDF]
Kabir MA, Chakma C.
europepmc +1 more source
Deep Learning for Age Estimation and Sex Prediction Using Mandibular-Cropped Cephalometric Images: Comparative Model Development and Validation Study. [PDF]
Handayani VW +5 more
europepmc +1 more source

