Prediction of soybean price in China using QR-RBF neural network model

Zhang, Dongqing; Zang, Guangming; Li, Jing; Ma, Ke; Liu, Huan

doi:10.1016/j.compag.2018.08.016

Cited by 67 publications

(48 citation statements)

References 27 publications

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“…Scholars from different science fields adapted ANNs as the tool for various areas of science including social sciences. Artificial neural networks are a powerful modelling technique for indicating the relationships between variables [36].…”

Section: Study Design and Samplingmentioning

confidence: 99%

Link between Financial Management Behaviours and Quality of Relationship and Overall Life Satisfaction among Married and Cohabiting Couples: Insights from Application of Artificial Neural Networks

Baryła-Matejczuk

Skvarciany

Cwynar

et al. 2020

IJERPH

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Background: To explain the link between household finances and the quality of the relationship between married or cohabitating partners and their life satisfaction, the Family Stress Model (FSM) was used and placed within the theoretical framework of the Couples and Finances Theory (CFT). Methods: The measures used to examine the relationship between partners were the Financial Management Behaviour Scale, the Marriage Questionnaire (KDM-2) adapted to a version for cohabitating couples, The Shared Goals and Values Scale, Harsh Start-up Scale, and the Satisfaction With Life Scale (SWLS). In order to find out the relationship between variables, artificial neural networks (ANN) were applied. The research was conducted on a sample of 500 couples living in Poland (384 married and 116 cohabitating couples). Results: The results indicate that overall life satisfaction is most influenced by fundamental, direct, current ways of dealing with the daily financial routine and by saving and investing behaviours. Credit management and insurance behaviours are the most important for the quality of the relationship between partners. Conclusions: The research shows that financial management behaviours have an impact on the quality of relationships as well as on the subjective well-being of people in a relationship, and their relationship dynamics. This finding may be used to highlight the psychological importance of financial management behaviours.

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Section: Study Design and Samplingmentioning

confidence: 99%

Link between Financial Management Behaviours and Quality of Relationship and Overall Life Satisfaction among Married and Cohabiting Couples: Insights from Application of Artificial Neural Networks

Baryła-Matejczuk

Skvarciany

Cwynar

et al. 2020

IJERPH

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“…The improvement of soybean production efficiency is conducive to ensuring the efficient development of China's agriculture. However, in recent years, with the rapid development of agricultural production technology, the efficiency of international soybean production has been continuously improved, while the frequent occurrence of agricultural disasters in China, the instability of soybean price [3], and the imperfect insurance system of soybean production have led to the low production efficiency of soybean in China. At the same time, new agricultural producers, including family farms, big growers, farmers' cooperatives and so on, have grown rapidly in recent years, which occupy an important position in the soybean producers as the main carrier of China's agricultural modernization development.…”

Section: Introductionmentioning

confidence: 99%

Analysis on Efficiency and Influencing Factors of New Soybean Producing Farms

Wang

Shi

2020

Agronomy

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The efficiency of new soybean producers is of great importance to the agricultural development of China. Based on the survey data of some counties (cities) in Heilongjiang, Jilin, Liaoning, and Inner Mongolia Autonomous Region, the efficiency of new soybean producers in these regions is calculated by means of the data envelopment analysis (DEA) model. Then, the Tobit model is used to select relevant explanatory variables to study the factors affecting the production efficiency, and relevant conclusions and suggestions are put forward. The results show that (1) in 2017, the new soybean producers’ average technical efficiency of soybean production in the research samples was 0.618, of which the average pure technical efficiency was 0.680 and the average scale efficiency was 0.872; (2) factors such as the degree of education, the soybean planting area, the degree of mechanization, and the soybean sales channel have positive impacts on the efficiency of new soybean producers, while the ones such as the stability of the soybean price, the difficulty in obtaining soybean market information, and the implementation of the soybean subsidy policy have negative impacts.

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“…Han et al investigated an automatic axon neural network (AANN) that can perform self-organizing architectures and weights while improving the network performance of nonlinear system modeling [9]. For the modeling of nonlinear systems in financial field, Zhang et al proposed a quantile regression-radial basis function (QR-RBF) neural network model to predict soybean prices [10]. These above-mentioned algorithms only considered the single hidden layer architecture.…”

Section: Proposed a Novel Learning Algorithm For Dynamic Fuzzy Neuralmentioning

confidence: 99%

An Improved Parallel MDBN With AVMD for Nonlinear System Modeling

Jin

Zhang

et al. 2020

IEEE Access

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Nonlinear system modeling using Deep Belief Network (DBN) is currently a research hotspot. However, the training process of DBN needs large amount of data to guarantee accuracy, and the traditional DBN may not meet the requirement of high-precision modeling. In this paper, we first improve the original DBN and Variational Mode Decomposition (VMD) algorithms, and on this basis, we then proposed a parallel Momentum Deep Belief Networks (MDBN) with Adaptive Variational Mode Decomposition (AVMD). Parallel AVMD-MDBN is an improved modeling method based on the deep learning model DBN. Firstly, a single raw dataset is decomposed into a specific number of sub-datasets using AVMD. Then these subdatasets are distributed among a number of improved MDBNs. A single raw dataset learning model and algorithm is extended to multiple feature extraction nodes to learn the characteristics of multiple subdatasets in parallel. Finally, the results of the multiple nodes are transmitted to the main feature extraction node to complete the regression calculation. In order to verify the effectiveness of the model, the proposed parallel AVMD-MDBN model is tested on a nonlinear dynamic system modeling, a Mackey-Glass timeseries prediction and a financial stock prediction. Our experimental results show that the proposed parallel AVMD-MDBN has better performances in terms of improving feature learning ability than that of other methods. INDEX TERMS Parallel momentum deep belief networks, adaptive variational mode decomposition, contrast divergence algorithm, nonlinear system modeling, financial stock prediction.

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Prediction of soybean price in China using QR-RBF neural network model

Cited by 67 publications

References 27 publications

Link between Financial Management Behaviours and Quality of Relationship and Overall Life Satisfaction among Married and Cohabiting Couples: Insights from Application of Artificial Neural Networks

Link between Financial Management Behaviours and Quality of Relationship and Overall Life Satisfaction among Married and Cohabiting Couples: Insights from Application of Artificial Neural Networks

Analysis on Efficiency and Influencing Factors of New Soybean Producing Farms

An Improved Parallel MDBN With AVMD for Nonlinear System Modeling

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