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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China
Tao Xiong, Chongguang Li, Yukun Bao
Neurocomputing (2017) Vol. 275, pp. 2831-2844
Closed Access | Times Cited: 154

Showing 1-25 of 154 citing articles:

Wholesale price forecasts of green grams using the neural network
Bingzi Jin, Xiaojie Xu
Asian Journal of Economics and Banking (2024)
Open Access | Times Cited: 104
Thermal coal futures trading volume predictions through the neural network
Bingzi Jin, Xiaojie Xu, Yun Zhang
Journal of Modelling in Management (2024)
Closed Access | Times Cited: 33
Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model
Xuebo Jin, Nian-Xiang Yang, Xiaoyi Wang, et al.
Sensors (2020) Vol. 20, Iss. 5, pp. 1334-1334
Open Access | Times Cited: 96
Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors
Zheng‐Xin Wang, Zhiwei Wang, Qin Li
Energy (2020) Vol. 200, pp. 117460-117460
Closed Access | Times Cited: 91
The Prediction of Dam Displacement Time Series Using STL, Extra-Trees, and Stacked LSTM Neural Network
Yangtao Li, Tengfei Bao, Jian Gong, et al.
IEEE Access (2020) Vol. 8, pp. 94440-94452
Open Access | Times Cited: 91
Deep Hybrid Model Based on EMD with Classification by Frequency Characteristics for Long-Term Air Quality Prediction
Xuebo Jin, Nian-Xiang Yang, Xiaoyi Wang, et al.
Mathematics (2020) Vol. 8, Iss. 2, pp. 214-214
Open Access | Times Cited: 82
Forecasting Agricultural Commodity Prices Using Model Selection Framework With Time Series Features and Forecast Horizons
Dabin Zhang, Shanying Chen, Liwen Ling, et al.
IEEE Access (2020) Vol. 8, pp. 28197-28209
Open Access | Times Cited: 80
STL-ATTLSTM: Vegetable Price Forecasting Using STL and Attention Mechanism-Based LSTM
Helin Yin, Jin Dong, Yeong Hyeon Gu, et al.
Agriculture (2020) Vol. 10, Iss. 12, pp. 612-612
Open Access | Times Cited: 74
Deep long short-term memory based model for agricultural price forecasting
Ronit Jaiswal, Girish Kumar Jha, Rajeev Ranjan Kumar, et al.
Neural Computing and Applications (2021) Vol. 34, Iss. 6, pp. 4661-4676
Closed Access | Times Cited: 58
Cooperative ensemble learning model improves electric short-term load forecasting
Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Gabriel Trierweiler Ribeiro, et al.
Chaos Solitons & Fractals (2022) Vol. 166, pp. 112982-112982
Closed Access | Times Cited: 49
Hybrid intelligent framework for carbon price prediction using improved variational mode decomposition and optimal extreme learning machine
Jujie Wang, Quan Cui, Maolin He
Chaos Solitons & Fractals (2022) Vol. 156, pp. 111783-111783
Closed Access | Times Cited: 48
Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India
Ranjit Kumar Paul, Md Yeasin, Pramod Kumar, et al.
PLoS ONE (2022) Vol. 17, Iss. 7, pp. e0270553-e0270553
Open Access | Times Cited: 48
Forecasting Agricultural Commodity Prices Using Dual Input Attention LSTM
Yeong Hyeon Gu, Jin Dong, Helin Yin, et al.
Agriculture (2022) Vol. 12, Iss. 2, pp. 256-256
Open Access | Times Cited: 42
Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products
Xiaojie Xu, Yun Zhang
Mineral Economics (2022) Vol. 36, Iss. 4, pp. 563-582
Closed Access | Times Cited: 40
Scrap steel price forecasting with neural networks for east, north, south, central, northeast, and southwest China and at the national level
Xiaojie Xu, Yun Zhang
Ironmaking & Steelmaking Processes Products and Applications (2023) Vol. 50, Iss. 11, pp. 1683-1697
Closed Access | Times Cited: 31
Edible oil wholesale price forecasts via the neural network
Xiaojie Xu, Yun Zhang
Energy Nexus (2023) Vol. 12, pp. 100250-100250
Open Access | Times Cited: 30
Wholesale Food Price Index Forecasts with the Neural Network
Xiaojie Xu, Yun Zhang
International Journal of Computational Intelligence and Applications (2023) Vol. 22, Iss. 04
Closed Access | Times Cited: 29
Hidden Markov guided Deep Learning models for forecasting highly volatile agricultural commodity prices
G. Avinash, V. Ramasubramanian, Mrinmoy Ray, et al.
Applied Soft Computing (2024) Vol. 158, pp. 111557-111557
Closed Access | Times Cited: 13
Predicting open interest in thermal coal futures using machine learning
Bingzi Jin, Xiaojie Xu
Mineral Economics (2024)
Closed Access | Times Cited: 11
A hybrid deep learning method for the prediction of ship time headway using automatic identification system data
Quandang Ma, Xu Du, Cong Liu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108172-108172
Open Access | Times Cited: 9
A new distributed time series evolution prediction model for dam deformation based on constituent elements
Mingchao Li, Yang Shen, Qiubing Ren, et al.
Advanced Engineering Informatics (2018) Vol. 39, pp. 41-52
Closed Access | Times Cited: 83
Agricultural product price forecasting methods: research advances and trend
Luyao Wang, Jianying Feng, Xiaojie Sui, et al.
British Food Journal (2020) Vol. 122, Iss. 7, pp. 2121-2138
Closed Access | Times Cited: 63
Optimized neural network combined model based on the induced ordered weighted averaging operator for vegetable price forecasting
Bo Li, Junqi Ding, Zhengqing Yin, et al.
Expert Systems with Applications (2020) Vol. 168, pp. 114232-114232
Closed Access | Times Cited: 51
Integrating data decomposition and machine learning methods: An empirical proposition and analysis for renewable energy generation forecasting
Song Ding, Huahan Zhang, Zui Tao, et al.
Expert Systems with Applications (2022) Vol. 204, pp. 117635-117635
Closed Access | Times Cited: 35
Random Forest and Feature Importance Measures for Discriminating the Most Influential Environmental Factors in Predicting Cardiovascular and Respiratory Diseases
Francesco Cappelli, Gianfranco Castronuovo, Salvatore Grimaldi, et al.
International Journal of Environmental Research and Public Health (2024) Vol. 21, Iss. 7, pp. 867-867
Open Access | Times Cited: 7
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