River water level prediction in coastal catchment using hybridized relevance vector machine model with improved grasshopper optimization

H Tao, NK Al-Bedyry, KM Khedher, S Shahid… - Journal of …, 2021 - Elsevier
Modelling river water level (WL) of a coastal catchment is much complex due to the tidal
influences on river WL. A hybrid machine learning model based on relevance vector …

[PDF][PDF] Forecasting the exchange rate of the Jordanian Dinar versus the US dollar using a Box-Jenkins seasonal ARIMA model

RS Al-Gounmeein, MT Ismail - International Journal of …, 2020 - ijmcs.future-in-tech.net
Abstract Seasonal Autoregressive Integrated Moving Average (SARIMA) model was fitted for
the time series data either to better understand the data or to predict the future points in the …

Linking singular spectrum analysis and machine learning for monthly rainfall forecasting

PO Bojang, TC Yang, QB Pham, PS Yu - Applied Sciences, 2020 - mdpi.com
Monthly rainfall forecasts can be translated into monthly runoff predictions that could support
water resources planning and management activities. Therefore, development of monthly …

Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia

JL Ng, YF Huang, SLS Yong, JC Lee… - AQUA—Water …, 2024 - iwaponline.com
Climate change is intensifying the occurrence of extreme rainfall events, drawing attention to
the importance of understanding the return period concept within the realm of extreme …

[PDF][PDF] China and Russia energy strategy development: Arctic LNG

A Steblyanskaya, X Qingchao, S Razmanova… - International Journal of …, 2021 - zbw.eu
Nowadays, the LNG market is a derivative of the traditional gas market and has certain
advantages over pipeline gas supplies. Many countries, including the Russian Federation …

Mean-Value-at-Risk Portfolio Optimization Based on Risk Tolerance Preferences and Asymmetric Volatility

Y Hidayat, T Purwandari, Sukono, IG Prihanto… - Mathematics, 2023 - mdpi.com
Investors generally aim to obtain a high return from their stock portfolio. However, investors
must realize that a high value-at-risk (VaR) is essential to calculate for this aim. One of the …

Forecasting of Poverty Data Using Seasonal ARIMA Modeling in West Java Province

DK Silalahi - JTAM (Jurnal Teori dan Aplikasi Matematika), 2020 - journal.ummat.ac.id
The government continues to carry out poverty reduction strategies in Indonesia, especially
in West Java Province. West Java Province is a province that has the most populous …

Improving models accuracy using kalman filter and holt-winters approaches based on arfima models

RS Al-Gounmeein, MT Ismail… - … Journal of Applied …, 2023 - search.proquest.com
The analysis, modeling, and forecast of oil prices are among the most important studies
related to global and local economic trends. Such studies are necessary to increase …

The SARIMA model-based monthly rainfall forecasting for the Turksvygbult Station at the Magoebaskloof Dam in South Africa

KB Tadesse, MO Dinka - Journal of Water and Land Development, 2022 - yadda.icm.edu.pl
Rainfall forecast information is important for the planning and management of water
resources and agricultural activities. Turksvygbult rainfall near the Magoebaskloof Dam …

Predicting the Water Inflow Into the Dam Reservoir Using the Hybrid Intelligent GP-ANN-NSGA-II Method

R Moeini, K Nasiri, SH Hosseini - Water Resources Management, 2024 - Springer
A key issue for effective management and operating of dam reservoirs is predicting the water
inflow values into dam reservoir. To address this subject, here, genetic programming (GP) is …