Browsing by Author "Xie, Naiming"

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    Data-based structure selection for unified discrete grey prediction model
    (Elsevier, 2019-06-24) Wei, Bao-lei; Xie, Naiming; Yang, Yingjie
    Grey models have been reported to be promising for time series prediction with small samples, but the diversity kinds of model structures and modelling assumptions restrains their further applications and developments. In this paper, a novel grey prediction model, named discrete grey polynomial model, is proposed to unify a family of univariate discrete grey models. The proposed model has the capacity to represent most popular homogeneous and non-homogeneous discrete grey models and furthermore, it can induce some other novel models, thereby highlighting the relationship between the models and their structures and assumptions. Based on the proposed model, a data-based algorithm is put forward to select the model structure adaptively. It reduces the requirement for modeler’s knowledge from an expert system perspective. Two numerical experiments with large-scale simulations are conducted and the results show its effectiveness. In the end, two real case tests show that the proposed model benefits from its adaptive structure and produces reliable multi-step ahead predictions.
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    Forecasting China's energy demand and self-sufficiency rate by grey forecasting model and Markov model
    (Elsevier, 2015) Xie, Naiming; Yuan, Chaoqing; Yang, Yingjie
    This paper applies novel models to forecast the developing trends of China’s energy production and consumption under the influence of China’s energy saving policy. An optimized single variable discrete grey forecasting model is adopted to forecast the total amount of energy production and consumption while a novel Markov approach based on quadratic programming model is proposed to forecast the trends of energy production and consumption structures. The proposed models are used to simulate China’s energy production and consumption during 2006–2011 and forecast its trends in 2015 and 2020. Results demonstrate that proposed models can effectively simulate and forecast the total amounts and structures of energy production and consumption. And by comparing with regression model, results show proposed model is a little better than regression in simulating and forecasting the case. Although the growth rate of energy consumption in China has decreased under the energy saving policy, total amount of energy consumption and the proportions of natural gas and other energies keep growing while the self-sufficiency rate of crude oil and natural gas continues to drop.
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    Grey Number Sequence Forecasting Approach for Interval Analysis: A case of China's Gross Domestic Product Prediction
    (Research Information Ltd, 2014) Xie, Naiming; Liu, Sifeng; Yuan, Chaoqing; Yang, Yingjie
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    Hybrid genetic algorithm based on bin packing strategy for the unrelated parallel workgroup scheduling problem
    (Springer, 2020-05-30) Su, Bentao; Xie, Naiming; Yang, Yingjie
    In this paper we focus on an unrelated parallel workgroup scheduling problem where each workgroup is composed of a number of personnel with similar work skills which has eligibility and human resource constraints. The most difference from the general unrelated parallel machine scheduling with resource constraints is that one workgroup can process multiple jobs at a time as long as the resources are available, which means that a feasible scheduling scheme is impossible to get if we consider the processing sequence of jobs only in time dimension. We construct this problem as an integer programming model with the objective of minimizing makespan. As it is incapable to get the optimal solution in the acceptable time for the presented model by exact algorithm, meta-heuristic is considered to design. A pure genetic algorithm based on special coding design is proposed firstly. Then a hybrid genetic algorithm based on bin packing strategy is further developed by the consideration of transforming the single workgroup scheduling to a strip-packing problem. Finally, the proposed algorithms, together with exact approach, are tested at different size of instances. Results demonstrate that the proposed hybrid genetic algorithm shows the effective performance.
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    New Progress of Grey System Theory in The New Millennium
    (Emerald, 2016) Liu, S.; Yang, Yingjie; Xie, Naiming; Forrest, J.
    Purpose – The purpose of this paper is to summarize the progress in grey system research during 2000- 2015, so as to present some important new concepts, models, methods and a new framework of grey system theory. Design/methodology/approach –The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “Kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of GM(1,1), such as Even Grey Model(EGM), Original Difference Grey Model(ODGM), Even Difference Grey Model(EDGM), Discrete Grey Model(DGM) and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well. Findings –The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper. Practical implications – A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science, and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate. Originality/value –The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section. Keywords Grey systems theory, Operations of grey numbers, Buffer operators, Grey forecasting models, Grey incidence analysis models, Grey cluster evaluation models, Grey decision models, Combined grey models, Grey control
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    Predicting the trend of infectious diseases using grey self-memory system model: a case study of the incidence of tuberculosis
    (Elsevier, 2021-11-22) Guo, Xiaojun; Shen, Houxue; Liu, Sifeng; Xie, Naiming; Yang, Yingjie; Jin, Jingliang
    Objectives The prediction and early warning of infectious diseases is an important work in the field of public health. This study constructed the grey self-memory system model to predict the incidence trend of infectious diseases affected by many uncertain factors. Study design The design of this study is a combination of the prediction method and empirical analysis. Methods By organically coupling the self-memory algorithm with the mean GM(1,1) model, the tuberculosis incidence statistics of China from 2004 to 2018 were selected for prediction analysis. Meanwhile, by comparing with the other traditional prediction methods, three representative accuracy check indexes (MSE, AME, MAPE) were conducting for error analysis. Results Owing to the multiple time-points initial fields, which replace the single time-points, the limitation of the traditional grey prediction model, which is sensitive to the initial value, is overcome in the self–memory equation. Consequently, compared with the mean GM model and other statistical methods, the grey self-memory model shows significant forecasting advantages, and its single-step rolling prediction accuracy is superior to other prediction methods. Therefore, the incidence of tuberculosis in China in the next year can be predicted as 55.30 (unit: 1/105). Conclusions The grey self-memory system model can closely capture the individual random fluctuation in the whole evolution trend of the uncertain system. It is appropriate for predicting the future incidence trend of infectious diseases and is worth popularizing to other similar public health prediction problems.
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    Research on Index System for Disabled Elders Evaluation and Grey Clustering Model Based on End-point Mixed Possibility Functions
    (Research Information Ltd, 2019-11-01) Liu, Sifeng; Fan, Yun; Yang, Yingjie; Tan, Xuerui; Fang, Zhigeng; Chen, Yequn; Zhang, Qin; Xie, Naiming; Yuan, Chaoqing; Xue, Qingyuan; Tao, Liangyan; Guo, Xiaojun
    An operational ability assessment system for older adults is of great help to address health and social challenges for ageing. In this paper, the main problems in currently available ADL and ability evaluation systems have been analyzed. The basic principles to build an index system for disability elders evaluation have been put forwarded. Then，an improved Barthel index system for ADL evaluation and a new older adults ability evaluation system consisted of 4 first-level indexes and 14 secondary indexes based on experts’ opinion and the ability assessment system for older adults by Ministry of Civil Affairs of China have been built. The grey clustering model based on end-point mixed triangular possibility function has been introduced. And three living examples of adults’ disability evaluation have been conducted. It is confirmed clearly that the three older adults belong to different categories of "severe disability", "mild disability", and "ability passable" respectively. The research results can be used as reference for government to formulate the elderly-care policies, to run and allocate the elderly-care resources, as well as reference for various nursing or elderly-care institutions.