Search

To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1,r), is built, and the modeling conditions and error checking methods of EGM(1,1,r) are studied. Then, EGM(1,1,r) is used to simulate and forecast China’s beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China’s beef consumption for the period from 2019–2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef. [ABSTRACT FROM AUTHOR]

Background: AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the ‘big data’ aggregated from Internet search engines, which contain users’ information on the concern or reality of their health status, provide a new opportunity for AIDS surveillance. This paper uses search engine data to monitor and forecast AIDS in China. Methods: A machine learning method, artificial neural networks (ANNs), is used to forecast AIDS incidences and deaths. Search trend data related to AIDS from the largest Chinese search engine, Baidu.com, are collected and selected as the input variables of ANNs, and officially reported actual AIDS incidences and deaths are used as the output variable. Three criteria, the mean absolute percentage error, the root mean squared percentage error, and the index of agreement, are used to test the forecasting performance of the ANN method. Results: Based on the monthly time series data from January 2011 to June 2017, this article finds that, under the three criteria, the ANN method can lead to satisfactory forecasting of AIDS incidences and deaths, regardless of the change in the number of search queries. Conclusions: Despite the inability to self-detect HIV/AIDS through online searching, Internet-based data should be adopted as a timely, cost-effective complement to a traditional AIDS surveillance system. [ABSTRACT FROM AUTHOR]

With the boost of online reviews, a large quantity of consumers' opinions on certain products and services are generated and spread over the internet, thus techniques of sentiment classification for online reviews rise in response to the requirement of retrieving valuable information. This paper is mainly focused on improving sentiment classification of Chinese online reviews through analysing and improving each step in supervised machine learning. At first, adjectives, adverbs, and verbs are selected as the initial text features. Then, three statistic methods (DF, IG and CHI) are utilised to extract features. At last, a Boolean method is applied to set weight to features and a support vector machine (SVM) is employed as the classifier. Several comparative experiments have been conducted on reviews of two domains: mobile phone (product) reviews and hotel (service) reviews. The experimental results indicate that part of speech (POS), the number of features, evaluation domain, feature extraction algorithm and kernel function of SVM have great influences on sentiment classification, while the number of training corpora has a little impact. In addition, further improvements of DF IG and CHI have been made, which demonstrate the theoretical significance and the practical value of this research. [ABSTRACT FROM AUTHOR]