Research on the Performance Evaluation of Logistics Enterprise Based on the Analytic Hierarchy Process

AbstractThe performance evaluation plays a more and more important role in the modern enterprise management, and the method of evaluation system on enterprise performance is always an important question in the theory and practice. So this paper set up a scientific, reasonable performance evaluation index system which was especially suitable for the small and medium third party logistics enterprise from the four levels of financial, customers, business and innovation. Meanwhile, according to the index system, it gave a performance evaluation with the Chinese access logistics corporation. The results showed that the construction of the index system was reasonable, and the evaluation results also were reliable

A Calibration Method for Wide Field Multicolor Photometric System

The purpose of this paper is to present a method to self-calibrate the spectral energy distribution (SED) of objects in a survey based on the fitting of an SED library to the observed multi-color photometry. We adopt for illustrative purposes the Vilnius (Strizyz and Sviderskiene 1972) and Gunn & Stryker (1983) SED libraries. The self-calibration technique can improve the quality of observations which are not taken under perfectly photometric conditions. The more passbands used for the photometry, the better the results. This technique has been applied to the BATC 15-passband CCD survey.Comment: LateX file, 1 PS file, submitted to PASP number 99-025 The English has been improved and some mistakes have been correcte

Research on Precipitation Prediction Model Based on Extreme Learning Machine Ensemble

Precipitation is a significant index to measure the degree of drought and flood in a region, which directly reflects the local natural changes and ecological environment. It is very important to grasp the change characteristics and law of precipitation accurately for effectively reducing disaster loss and maintaining the stable development of a social economy. In order to accurately predict precipitation, a new precipitation prediction model based on extreme learning machine ensemble (ELME) is proposed. The integrated model is based on the extreme learning machine (ELM) with different kernel functions and supporting parameters, and the submodel with the minimum root mean square error (RMSE) is found to fit the test data. Due to the complex mechanism and factors affecting precipitation change, the data have strong uncertainty and significant nonlinear variation characteristics. The mean generating function (MGF) is used to generate the continuation factor matrix, and the principal component analysis technique is employed to reduce the dimension of the continuation matrix, and the effective data features are extracted. Finally, the ELME prediction model is established by using the precipitation data of Liuzhou city from 1951 to 2021 in June, July and August, and a comparative experiment is carried out by using ELM, long-term and short-term memory neural network (LSTM) and back propagation neural network based on genetic algorithm (GA-BP). The experimental results show that the prediction accuracy of the proposed method is significantly higher than that of other models, and it has high stability and reliability, which provides a reliable method for precipitation prediction

What Affects Chinese Residents’ Perceptions of Climate Change?

The theme of global sustainable development has changed from environmental management to climate governance, and relevant policies on climate governance urgently need to be implemented by the public. The public understanding of climate change has become the prerequisite and basis for implementing various climate change policies. In order to explore the affected factors of climate change perception among Chinese residents, this study was conducted across 31 provinces and regions of China through field household surveys and interviews. Combined with the residents&rsquo; perception of climate change with the possible affected factors, the related factors affecting Chinese residents&rsquo; perception of climate change were explored. The results show that the perceptive level of climate change of Chinese residents is related to the education level and the household size of residents. Improving public awareness of climate change risk in the context of climate change through multiple channels will also help to improve residents&rsquo; awareness of climate change. On the premise of improving the level of national education, improving education on climate change in school education and raising awareness of climate change risk among dependents will help to improve the level of Chinese residents&rsquo; awareness of climate change, which could be instrumental in promoting public participation in climate change mitigation an dadaptation actions</p