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Article
Publication date: 6 November 2017

Shouhui Wang, Jianguo Dai, Qingzhan Zhao and Meina Cui

Many factors affect the emergence and development of crop diseases and insect pests. Traditional methods for investigating this subject are often difficult to employ and produce…

Abstract

Purpose

Many factors affect the emergence and development of crop diseases and insect pests. Traditional methods for investigating this subject are often difficult to employ and produce limited data with considerable uncertainty. The purpose of this paper is to predict the annual degree of cotton spider mite infestations by employing grey theory.

Design/methodology/approach

The authors established a GM(1,1) model to forecast mite infestation degree based on the analysis of historical data. To improve the prediction accuracy, the authors modified the grey model using Markov chain and BP neural network analyses. The prediction accuracy of the GM(1,1), Grey-Markov chain, and Grey-BP neural network models was 84.31, 94.76, and 96.84 per cent, respectively.

Findings

Compared with the single grey forecast model, both the Grey-Markov chain model and the Grey-BP neural network model had higher forecast accuracy, and the accuracy of the latter was highest. The improved grey model can be used to predict the degree of cotton spider mite infestations with high accuracy and overcomes the shortcomings of traditional forecasting methods.

Practical implications

The two new models were used to estimate mite infestation degree in 2015 and 2016. The Grey-Markov chain model yielded respective values of 1.27 and 1.15, whereas the Grey-BP neural network model yielded values 1.4 and 1.68; the actual values were 1.5 and 1.8.

Originality/value

The improved grey model can be used for medium- and long-term predictions of the occurrence of cotton spider mites and overcomes problems caused by data singularity and fluctuation. This research method can provide a reference for the prediction of similar diseases.

Details

Grey Systems: Theory and Application, vol. 7 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 31 December 2015

ENZE LIU

The purpose of this paper is to provide a historical review of China’s anti-corruption efforts, from the ancient period of Chinese slavery societies to the late 1970s before China…

1100

Abstract

Purpose

The purpose of this paper is to provide a historical review of China’s anti-corruption efforts, from the ancient period of Chinese slavery societies to the late 1970s before China launched its profound economic reform, under the current status of the harsh crusade against corruption that the Chinese new leadership initiated.

Design/methodology/approach

This paper is mainly based on a great deal of historical literature and empirical findings, with relevant comparative analysis on policies and regulations between various periods of China.

Findings

The phenomenon of corruption has existed in Chinese history for thousands of years, throughout Chinese slavery societies, feudal societies, republic period and the People’s Republic of China (PRC). Anti-corruption laws formed an important part of ancient Chinese legal system, and each dynasty has made continuous and commendable progress on fighting such misconduct. Innumerable initiatives have also been taken by the ruling party Chinese Communist Party (CCP) since the founding of the PRC. The PRC government created various specially designed government organizations and a series of updated regulations for preventing economic crimes. They have realized that periodic movements against corruption would no longer be helpful, and the paramount issue nowadays is indeed how bold the leaders are in striking out those unhealthy tendencies.

Originality/value

This paper fills in the blanks in the Western world with a comprehensive description of, and comments on, the historical efforts on China’s corruption and economic crime prevention. It also, in various ways, provides meaningful information that links to China’s current furious war against corruption.

Details

Journal of Financial Crime, vol. 23 no. 1
Type: Research Article
ISSN: 1359-0790

Keywords

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