Πλοήγηση ανά Θέμα "Forecasting"
Αποτελέσματα 21-40 από 125
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Comparison of ARIMA and Transfer Function (TF) models in Water Temperature simulation in dam - Lake Thesaurus, eastern Macedonia, Greece
(2010)In the present work, two modelling and forecasting techniques were evaluated on the basis of: a) their efficiency to forecast and b) their ability to utilize auxiliary environmental information: ARIMA and Transfer Function ... -
A Comparison of Feature Selection Techniques for Neural Network Based Load Forecasting
(2019)The performance of neural networks in load forecasting tasks is highly influenced by the selection of the inputs. This selection is either problem specific or is relied on the literature. The scope of the present study is ... -
The contribution of open big data sources and analytics tools to sustainable urban mobility
(2019)Sustainable urban mobility is one of the top priorities in European Union and worldwide, as there is an intense tendency of population density increase in urban areas, which results in traffic, economic, environmental and ... -
Cost evaluation of noise barriers implementation in the Greek highway network
(2016)Transportation side effects like, noise, accidents and air pollution and others are a cost that arises from an economic transaction and that falls on people who do not participate in the transaction. Among those side ... -
Daily multivariate forecasting of water demand in a touristic island with the use of artificial neural network and adaptive neuro-fuzzy inference system
(2016)Water demand forecast has emerged as an imperative component of intelligent Internet and Communication Technologies based methodologies of water management. The need of increased time resolution of forecast in order to ... -
Day-ahead natural gas demand forecasting in hourly resolution
(2021)Natural Gas (NG) demand forecasting is a research topic that starts to gather the attention of scholars, research institutions, utilities, retailers and other interested parties. Accurate predictions of future needs for ... -
Deep Bidirectional and Unidirectional LSTM Neural Networks in Traffic Flow Forecasting from Environmental Factors
(2021)The application of deep learning techniques in several forecasting problems has been increased the last years, in many scientific fields. In this research, a deep learning structure is proposed, composed mainly of double ... -
Deep learning in water resources management: The case study of Kastoria lake in Greece
(2021)The effects of climate change on water resources management have drawn worldwide attention. Water quality predictions that are both reliable and precise are critical for an effective water resources management. Although ... -
Energy Use Forecasting with the Use of a Nested Structure Based on Fuzzy Cognitive Maps and Artificial Neural Networks
(2022)The aim of this paper is to present a novel approach to energy use forecasting. We propose a nested fuzzy cognitive map in which each concept at a higher level can be decomposed into another fuzzy cognitive map, multilayer ... -
Enhanced short-term load forecasting using artificial neural networks
(2021)The modernization and optimization of current power systems are the objectives of research and development in the energy sector, which is motivated by the ever-increasing electricity demands. The goal of such research and ... -
Error Compensation Enhanced Day-Ahead Electricity Price Forecasting
(2022)The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards ... -
Estimation of the prediction error correlation model in bayesian model updating
(2013)In Bayesian model updating, probability density functions of model parameters are updated accounting both for the information contained in the data and for uncertainties present in the measurements and model predictions, ... -
Estimation of the recharging rate of groundwater using random forest technique
(2020)Accurate knowledge of the recharging rate is essential for several groundwater-related studies and projects mainly in the water scarcity regions. In this study, a comparison between different methods of soft computing-based ... -
ETH analysis and predictions utilizing deep learning
(2020)This paper attempts to provide a data analysis of cryptocurrency markets. Such markets have been developed rapidly and their volatility poses significant research challenges and justifies intensive behavior analysis. For ... -
Evaluation of the AWR-WRF model configuration at high resolution over the domain of Greece
(2018)This study is a first attempt to obtain high resolution simulations of present climate in Greece, by applying dynamical downscaling using the Advanced Weather Research and Forecasting numerical model (WRF-ARW). We performed ... -
An explainable machine learning model for material backorder prediction in inventory management
(2021)Global competition among businesses imposes a more effective and low-cost supply chain allowing firms to provide products at a desired quality, quantity, and time, with lower production costs. The latter include holding ... -
An explainable machine learning pipeline for backorder prediction in inventory management systems
(2021)Backorders occur when a product is out of stock, but the costumer is willing to place an order for this product and wait until it will be available for shipment instead of purchasing another. It is an important part of the ... -
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in Greece
(2019)This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim ... -
Extreme Interval Electricity Price Forecasting of Wholesale Markets Integrating ELM and Fuzzy Inference
(2019)The electricity wholesale market is inherently volatile in a deregulated market structure where market participants like power generators and retailors drive the price of electricity. Timely forecasting of the wholesale ... -
Fatigue crack growth prediction in 2xxx AA with friction stir weld HAZ properties
(2016)An analytical model is developed to predict fatigue crack propagation rate under mode I loading in 2024 aluminum alloy with FSW HAZ material characteristics. Simulation of the HAZ local properties in parent 2024 AA was ...