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Christy Pérez-Albornoz, Ángel Hernández-Gómez, Victor Ramirez and Damien Guilbert
Installation of new wind farms in areas such as the north coast of the Yucatan peninsula is of vital importance to face the local energy demand. For the proper functioning of these facilities it is important to perform wind data analysis, the data having...
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Asha Jayasree, Santhosh Kumar Sasidharan, Rishidas Sivadas and Jayan A. Ramakrishnan
Rainfall forecasting is critical for the economy, but it has proven difficult due to the uncertainties, complexities, and interdependencies that exist in climatic systems. An efficient rainfall forecasting model will be beneficial in implementing suitabl...
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Yaxi Su, Chaoran Cui and Hao Qu
Time series prediction has been studied for decades due to its potential in a wide range of applications. As one of the most popular technical indicators, moving average summarizes the overall changing patterns over a past period and is frequently used t...
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Shurui Fan, Dongxia Hao, Yu Feng, Kewen Xia and Wenbiao Yang
Accurate and reliable air quality predictions are critical to the ecological environment and public health. For the traditional model fails to make full use of the high and low frequency information obtained after wavelet decomposition, which easily lead...
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Agaraoli Aravazhi
Recent developments in machine learning and deep learning have led to the use of multiple algorithms to make better predictions. Surgical units in hospitals allocate their resources for day surgeries based on the number of elective patients, which is mos...
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Yelyzaveta Meleshko
Pág. 52 - 57
The subject matter of the research is the process of identifying information attacks on the recommendation system. The goal of this work is to develop a method for detecting information attack objects in a recommendation system based on the analysis of t...
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Kamyar Sabri-Laghaie, Saeid Jafarzadeh Ghoushchi, Fatemeh Elhambakhsh and Abbas Mardani
A completely new economic system is required for the era of Industry 4.0. Blockchain technology and blockchain cryptocurrencies are the best means to confront this new trustless economy. Millions of smart devices are able to complete transparent financia...
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Jaehong Yu, Seoung Bum Kim, Jinli Bai and Sung Won Han
Recently, a number of data analysists have suffered from an insufficiency of historical observations in many real situations. To address the insufficiency of historical observations, self-starting forecasting process can be used. A self-starting forecast...
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Haibing Hu, Bo Zhang, Dongjian Xu and Guo Xia
Detecting the defects of a battery on the surface and edge has always been difficult, especially for concave and convex ones, thereby seriously affecting its quality. Thus, sub-regional Gaussian and moving average filtering are innovatively proposed in t...
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Chun-Feng Hao, Jun Qiu, Fang-Fang Li
Pág. 1 - 16
With the rapid economic growth in China, a large number of hydropower projects have been planned and constructed. The sediment deposition of the reservoirs is one of the most important disputes during the construction and operation, because there are man...
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Chun-Feng Hao, Jun Qiu and Fang-Fang Li
With the rapid economic growth in China, a large number of hydropower projects have been planned and constructed. The sediment deposition of the reservoirs is one of the most important disputes during the construction and operation, because there are man...
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Thiago Raymon Cruz Cacique da Costa,Vinicius Amorim Sobreiro
Indicadores de Análise Técnica - AT têm sido utilizados para recomendar oportunidades de compra e venda no mercado de ação. Recentemente, esses indicadores têm servido como diretrizes nos algoritmos de programas que operam de maneira autônoma no mercado ...
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Karin Kandananond
Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods?autoregressive integrated...
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VIDAL L. MATEOS,JOSÉ A. GARCÍA,ANTONIO SERRANO,MARÍA DE LA CRUZ GALLEGO
In order to improve the results given by Autoregressive Moving-Average (ARMA) modeling for the monthly accumulated rainfall series taken at 19 observatories of the Iberian Peninsula, a Discrete Linear Transfer Function Noise (DLTFN) model was appli...
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Fadhlan Zuhdi,Rizqi Sari Anggraini,Rachmiwati Yusuf
Pág. 40 - 50
AbstractRubber has long been become a mainstay of Indonesian exports along with oil palm, coffee and tea. As a commodity that has increasing world demand, rubber exports are given priority. This must be responded quickly by the government in order ...
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Yuqing Gao, Khalid M. Mosalam, Yueshi Chen, Wei Wang and Yiyi Chen
Auto-regressive (AR) time series (TS) models are useful for structural damage detection in vibration-based structural health monitoring (SHM). However, certain limitations, e.g., non-stationarity and subjective feature selection, have reduced its wide-sp...
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Abdelkader Sahed, Mohammeed Mekidiche, Hacen Kahoui
Pág. 1 - 13
In this study, the Fuzzy Auto-Regressive Integrated Moving Average (FARIMA) Model has been used to predict gold prices, The main objective was to estimate the fractional parameters by using the fuzzy regression method of TANAKA. The prediction accuracy o...
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Abhiram Dash, A. Mangaraju, Suman ., Pradeep Mishra
Pág. Page:15 - 24Abstract
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Ernest Kissi, Theophilus Adjei-Kumi, Peter Amoah, Jerry Gyimah
Pág. 70 - 82
Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision....
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H. S. Umar, A. A. Girei, O. A. Aliyu
Pág. Page:1 - 6Abstract
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