Search Results - Time-series forecasting algorithm performance prediction

Towards understanding the importance of time-series features in automated algorithm performance prediction by Petelin, Gašper, Cenikj, Gjorgjina, Eftimov, Tome

“…’ performance depends on the time-series properties, as well as the properties of the forecasting algorithms…”
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Assessing the Applicability of the LTSF Algorithm for Streamflow Time Series Prediction: Case Studies of Dam Basins in South Korea by Park, Jiyeon, Shin, Ju-Young, Kim, Sunghun, Kwon, Jihye

“… Although long-term time series forecasting (LTSF) algorithms have shown strong performance in other domains, their applicability to hydrological inflow prediction has not yet been systematically assessed…”
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Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms by Mochinski, Marcos Alberto, Paul Barddal, Jean, Enembreck, Fabricio

“…This paper proposes a hybrid ensemble learning approach that combines statistical and data stream mining algorithms to obtain better forecasting performance in multiple time series prediction problems…”
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Day-ahead power forecasting in a large-scale photovoltaic plant based on weather classification using LSTM by Gao, Mingming, Li, Jianjing, Hong, Feng, Long, Dongteng

“…) is significant for real-time power dispatching. Day-ahead power output time-series forecasting methods are proposed in this paper, in which ideal weather type and non-ideal weather types have been separately discussed…”
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EnsPKDE&IncLKDE: a hybrid time series prediction algorithm integrating dynamic ensemble pruning, incremental learning, and kernel density estimation by Zhu, Gangliang, Dai, Qun

“… This paper proposes a hybrid Time Series Prediction (TSP) algorithm to implement one-step-ahead prediction task, integrating Dynamic Ensemble Pruning (DEP…”
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Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach by Xue, Rui, Chen, Shukai, Sun, Jian

“… After the correlation, periodicity, and stationarity analyses, time series models were constructed. Particularly, the heteroscedasticity of time series was explored to achieve better prediction performance…”
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Differential Convolutional Fuzzy Time Series Forecasting by Zhan, Tianxiang, He, Yuanpeng, Deng, Yong, Li, Zhen

“…Fuzzy time series forecasting (FTSF) is a typical forecasting method with wide application…”
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Interpretable wind speed prediction with multivariate time series and temporal fusion transformers by Wu, Binrong, Wang, Lin, Zeng, Yu-Rong

“… This study puts forward a unique forecasting methodology that incorporates notable decomposition techniques, multifactor interpretable forecasting models, and optimization algorithms…”
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Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM by Huang, Xiaoqiao, Li, Qiong, Tai, Yonghang, Chen, Zaiqing, Liu, Jun, Shi, Junsheng, Liu, Wuming

“… This paper proposes a novel TSF-CGANs (time series forecasting based on CGANs, TSF-CGANs) algorithm…”
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Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization by Chen, Jie, Zeng, Guo-Qiang, Zhou, Wuneng, Du, Wei, Lu, Kang-Di

“…•A novel nonlinear-learning ensemble of deep learning time series prediction is proposed for wind speed forecasting…”
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A comparative machine learning study for time series oil production forecasting: ARIMA, LSTM, and Prophet by Ning, Yanrui, Kazemi, Hossein, Tahmasebi, Pejman

“… This paper presents a machine learning-based time series forecasting method, which considers the existing data as time series and extracts the salient characteristics of historical data to predict…”
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Big Data Driven Marine Environment Information Forecasting: A Time Series Prediction Network by Wen, Jiabao, Yang, Jiachen, Jiang, Bin, Song, Houbing, Wang, Huihui

“… This article proposes a semisupervised prediction model, which exploits the improved unsupervised clustering algorithm to establish the fuzzy partition function, and then utilize the neural network…”
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A combined forecasting model for time series: Application to short-term wind speed forecasting by Liu, Zhenkun, Jiang, Ping, Zhang, Lifang, Niu, Xinsong

“…[Display omitted] •An advanced combined model is developed for short-term wind speed forecasting…”
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Machine learning-based time series models for effective CO2 emission prediction in India by Kumari, Surbhi, Singh, Sunil Kumar

“… India’s detrimental CO 2 emission effect with the prediction of CO 2 emission for the next 10 years based on univariate time-series data from 1980 to 2019…”
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Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting by Barrera-Animas, Ari Yair, Oyedele, Lukumon O., Bilal, Muhammad, Akinosho, Taofeek Dolapo, Delgado, Juan Manuel Davila, Akanbi, Lukman Adewale

“… Therefore, approaches that use Machine Learning algorithms in conjunction with time-series data are being explored as an alternative to overcome these drawbacks…”
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Online fuzzy time series analysis based on entropy discretization and a Fast Fourier Transform by Chen, Mu-Yen, Chen, Bo-Tsuen

“…Fuzzy time series analysis has been used successfully for forecasting in various domains including stock performance, academic enrollment, temperature, and traffic patterns…”
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Financial time series forecasting model based on CEEMDAN and LSTM by Cao, Jian, Li, Zhi, Li, Jian

“…) with the long short-term memory (LSTM). The financial time series is a kind of non-linear and non-stationary random signal, which can be decomposed into several intrinsic mode functions of different time scales by the original EMD…”
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Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning by Spadon, Gabriel, Hong, Shenda, Brandoli, Bruno, Matwin, Stan, Rodrigues-Jr, Jose F., Sun, Jimeng

“…Time-series forecasting is one of the most active research topics in artificial intelligence…”
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Application of Deep Learning Architectures for Satellite Image Time Series Prediction: A Review by Moskolaï, Waytehad Rose, Abdou, Wahabou, Dipanda, Albert, Kolyang

“…, anomaly detection, and prediction. Several traditional machine learning algorithms have been developed and successfully applied to time series for predictions…”
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A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction by Jallal, Mohammed Ali, González-Vidal, Aurora, Skarmeta, Antonio F., Chabaa, Samira, Zeroual, Abdelouhab

“… The accuracy of the prediction of buildings’ energy consumption is being tackled using existing artificial intelligence techniques…”
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