Grey System GM Research Articles

INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS

The current potential market demand with ever-changing situations and conditions must be managed properly to find out the potential market demand in the future. Rumah Warna Yogyakarta is one of the manufacturing industry players that has experienced fluctuations in market demand, even tending to decline from the end of 2021 to mid-2022. Data was obtained from the database and direct interviews with Rumah Warna in Yogyakarta from November 2021 to November 2022. This study aims to determine the prediction of product demand for Rumah Warna Yogyakarta in the next period, so that companies can carry out production planning strategies to minimize production cost. Product demand prediction is carried out using the Grey System method of the GM (1,1) model. Then proceed with the heuristic aggregate planning method that focuses on overtime control and subcontracting control. Based on the results of the analysis, the Grey System GM (1,1) method produces good prediction accuracy of 9.231%. The best aggregate planning method is the overtime control where Rumah Warna Yogyakarta can reduce costs by Rp 351,258,758 when compared to the subcontracting control method.

Grey System Model GM (1,1) for Predicting Student Performance

The purpose of this study is to predict student quiz assignments in the General Physics I course during one semester using the Grey system GM (1,1) model. The prediction model integrates the first-order two-variable grey differential equation model from the Grey system theory. Additionally, a MATLAB program for the GM (1,1) prediction model was developed. The predicted results were compared with the original GM (1,1) model, showing good agreement.

Study of Mechanics and Durability of Non-Spontaneous Combustion Coal Gangue Coarse-Aggregate High-Performance Concrete.

The coal gangue coarse-aggregate content in ordinary concrete should not be too large. In order to further improve the utilization rate of coal gangue coarse aggregate, this study used the principle of "strong wrapped weak" to prepare high-performance concrete. This study considered four factors, namely, water-binder (W/B) ratios, non-spontaneous combustion coal gangue (NCCG) coarse-aggregate contents, fly ash-slag mass ratios, and silica fume coating to prepare high-performance concrete. The workability, mechanical, and durability properties were studied, and the changes in the interfacial transition zone (ITZ) of concrete before and after sulfate attack and freeze-thaw cycles were analyzed based on the SEM test. The life prediction of NCCG coarse-aggregate high-performance concrete was carried out based on the grey system GM(1,1) prediction model. The results show that the NCCG coarse-aggregate contents have the greatest effect on compressive strength, sulfate resistance, and frost resistance. The W/B ratio has the greatest effect on the anti-carbonization properties. Fly ash-slag mixing can obtain better durability. Considering the effect on the design service life of high-performance concrete, NCCG coarse aggregate is used to prepare high-performance concrete in North China, and the recommended content is 60%; in the Northwest and Northeast regions, the recommended content is 45%. This study provides a basis for the preparation of high-performance concrete with NCCG coarse aggregate.

Calculation of the Rate of Reaching the Standard of Beijing Citizens' Scientific Quality During the 14th Five Year Plan Period——Based on the L-Q GM(1,1)

As one of the four centers, Beijing is an important part of the national innovation system and an important driving force of social development. The scientific quality of Beijing citizens has become an important yardstick of contemporary society. By interpolating the discontinuous sample data of Beijing citizens' scientific quality compliance rate from 2015 to 2020 and using the grey system GM (1,1) model improved by the L-Q method to calculate, the Beijing citizens' scientific quality compliance rate from 2021 to 2025 is obtained. The results show that the Beijing citizens' scientific quality compliance rate is steadily rising, and will exceed 30% from 2024 and reach 35.26% by 2025, This is far beyond the target that the proportion of Chinese citizens with scientific quality should exceed 15% by 2025 and the long-term goal of 2035 in the outline of the action plan for the scientific quality of the whole people (2021-2035). At the same time, this paper gives suggestions to improve Beijing's science popularization work: measure the development trend of the compliance rate with the small sample method to guide the work, promote the coordinated development of new infrastructure and traditional infrastructure in the field of science popularization, strengthen the systematic promotion of science popularization, and pay attention to the accurate supply of science popularization services.

Forecast of Water Structure Based on GM (1, 1) of the Gray System

A forecast approach of water structure based on GM (1, 1) of the gray system is proposed. Based on economic and water information of Hebei Province from 2000 to 2018, the water use structure of Hebei’s industrial sector form 2019 to 2030 is forecasted according to the composition data and gray system GM (1, 1) model. The forecasting results by the proposed approach shows that the water structure of the tertiary industry has changed from 62.8 : 10.3 : 26.9 in 2018 to 60.5 : 10.2 : 29.3 in 2030. The proportion of water used in the primary and secondary industries has decreased slightly, the proportion of water used in the tertiary industry has increased, and the proportion of water used in the tertiary industry has not changed significantly.

Analysis of Response to the Wild Hornet Crisis Based on the SIR Model

In this paper, we propose 4 theoretical models to deal with the wild hornet crisis. First, we use ORIGIN to visualize the distribution of wild wasps. Using the least square method and the grey system GM (1, 1), we establish a theoretical model to predict the propagation of wild wasps over time and analyze the accuracy of the model. However, the accuracy of our model is not very high, which results from the influence of many factors such as climate and human. Secondly, we use convolution neural network to recognize the images. With the increase of network depth, the accuracy rate reaches a bottleneck, which can help predict mistaken classification. We also use the SIR infectious disease model based on the dataset file provided. In the model, we mark the confirmed giant hornet as the infected state I (infected), mark the nonwild wasp as the removed state R (removed, refractory, or recovered), and mark the unclassified and unverified wild wasp as the susceptible state S (susceptible). A model to predict the possibility of misclassification was established by considering the normal death of wild wasp. Thirdly, by analogy with the SIR model, when the epidemic occurs, people pay more attention to the infected person. Thus, the SIR model will lead to the most likely positive sightings. Then, in order to ensure the timeliness and accuracy, the model must be updated once a year by changing or adding parameter according to local conditions. Finally, by establishing an optimized SIR infectious disease model, we added the factor of the Washington state’s control of wild wasps. The analysis shows that the number of infected I (i.e., wild wasps) has tended to zero after 250 days, so it can be proved that the Washington state has eliminated the pest.

Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas

The article presents the methodology of isolating aperiodic phenomena constituting the basis of the energy balance of vehicles for the analysis of electromobility system indicators. The symptom observation matrix (SOM) and experimental input data are used to analyze periodic phenomena symptoms. The multidimensional nature of the engine efficiency shortage has been well defined and analyzed in terms of errors in the general model using neural networks, singular value decomposition, and principal component analysis. A more difficult task is the analysis of a multidimensional decision-making process. The research used a data fusion method and the concept of symptom reliability, which is applied to the generalized failure symptom obtained by applying the singular value decomposition (SVD). The model research has been based on the gray system theory (GST) and GM forecasting models (1,1). Input data were obtained from the assessment of driving cycles and analysis of the failure frequency for 1200 vehicles and mileage of 150,000 km. Based on this analysis, it can be concluded that with the current infrastructure and operating costs and the frequency of failure of PHEV and BEV drives, ICEV vehicles are unrivaled in terms of their operating costs.

Research on Forecasting the Number of Tourists in Anyang Based on Grey System GM (1, 1)

Research on Forecasting the Number of Tourists in Anyang Based on Grey System GM (1, 1)

Application of GM (1,1) and Seasonal Cross-Trend Model in the Forecast of Tourist Population in Sanya

In recent years, tourism has been playing an increasingly prominent role in China's economic development, especially in the tourism-oriented cities. Therefore, Sanya has been selected for research and analysis in this paper to reveal the tourism development law of Sanya. Based on gray system GM (1,1) and seasonal cross-trend model, this article analyzes domestic annual and monthly tourist numbers in Sanya, reveals their development rules, and forecasts their future development trends with this model.

Investigation of Karst Spring Flow Cessation Using Grey System Models

Karst aquifers are prominent sources of water worldwide; they store large amounts of water and are known for their beautiful springs. However, extensive groundwater development and climate variation has resulted in a decline in the flow of most karst springs; some have even dried up. In order to obtain a better understanding of the factors contributing to this development, this study introduced grey system models, which quantified spring flow, taking Jinci Springs (China), which dried up in May 1994, as an example. Based on the characteristics of Jinci Springs, spring flow was divided into two stages: first (1954–1960), when the spring flow was affected only by climate variation; and second (1961–1994), when the flow was impacted by both climate variation and anthropogenic activities. The results showed that Jinci Springs flow had a strong relationship with precipitation occurring one year and three years earlier in the first stage. Subsequently, a grey system GM (1,3) model with one-year and three-year lags was set up for the first stage. By using the GM (1,3) model, we simulated the spring flow in the second stage under effects of climate variation only. By subtracting the observed spring flow from the simulated flow, we obtained the contribution of anthropogenic activities to Jinci Springs’ cessation. The contribution of anthropogenic activities and climate variation to the decline was 1.46 m3/s and 0.62 m3/s, respectively. Finally, each human activity that caused the decline was estimated. The methods devised herein can be used to describe karst hydrological processes that are under the effects of anthropogenic activities and climate variation.

Measurement forecast of anomalous threshold voltages in BCD LV submicron n-MOSFETs with two artificial intelligence methods

Abstract In this study, two intelligent methodologies were used to estimate the anomalous threshold-voltage (V th ) measured behaviors in sub-micrometer Bipolar-CMOS-DMOS (BCD) low-voltage (LV) MOSFETs by using the grey system (GS) GM (1,1) model and a fuzzy-neural network (FNN). This paper describes the implementation procedures of these two models for making V th predictions. Moreover, discrepant comparisons between the GS and FNN output data are also demonstrated. Eventually, only the outputs of FNN can have the complex action of reverse short-channel property. Then, it will be developed to analyze the V th inclination of submicron n-channel MOSFETs due to the device geometric effect. A comparison between the measured characteristics of V th and the characteristics of V th predicted by the FNN shows good agreement for a wide range of channel lengths, widths and bias conditions. And, the maximum error percentage was less than 0.08%. As such, the developed procedure may be well suited for the data estimation of the complicated BSIM-model parameters in foundry fabrications.

普陀山岛旅游生态安全发展趋势预测

PDF HTML阅读 XML下载 导出引用 引用提醒 普陀山岛旅游生态安全发展趋势预测 DOI: 10.5846/stxb201510232147 作者: 作者单位: 宁波大学旅游系 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41301141）；宁波大学区域经济与社会发展研究院海洋专项研究项目（HYS1205） Developmental trend forecasting of tourism ecological security trends: the case of Mount Putuo Island Author: Affiliation: Tourism Department of college of liberal arts,Ningbo university Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:科学地预测海岛目的地旅游生态安全发展趋势，对促进海岛旅游经济和生态环境协调发展具有重要的理论意义和实践价值。基于可持续发展的视角，建立了由承载力-支持力-吸引力-延续力和发展力（CSAED模型）子系统构成的普陀山旅游生态安全指标体系，并在灰色系统GM（1，1）模型和RBF神经网络模型比较选优的基础上，对普陀山岛旅游生态安全发展趋势进行了预测。研究结果表明：（1）和灰色系统GM（1，1）模型相比，RBF神经网络模型的Pearson相关系数和误差均方根值更优，可更精确地拟合普陀山岛旅游生态安全发展趋势；（2）2015-2020年，普陀山岛旅游生态安全指数的RBF神经网络模型预测结果由0.7017增加至0.8135，安全等级由比较安全上升至非常安全。研究结果可为维护普陀山岛旅游生态安全提供决策依据。 Abstract:The study of tourism ecological security is a core problem in the research of sustainable tourism development. It has important theoretical significance and practical value for coordinated development of island tourism economy and the ecological environment. It can be used to scientifically predict island destination development trends of tourism ecological security. Tourism destination can be regarded as an organism with a complex ecosystem. To our knowledge, once the function is disordered, the destination must be considered threatened. The purpose of this paper was to construct a tourism ecological safety index system based on the five subsystems, including "Carrying Capability", "Supporting Capability", "Attraction Capability", "Evolution Capability", and "Developing Capability" (Known as the CSAED model). Based on the sustainable development perspective, and the comprehensive, dynamic principle; this paper uses Mount Putuo Island in Zhejiang Province as an example, and constructs a tourism ecological safety index system based on the subsystems of carrying capacity, attraction capability, evolution capability, and development capability (CSAED model). The paper used the Grey system GM (1, 1) model and the radial basis function (RBF) neural network model to forecast tourism ecological safety in Mount Putuo Island. The results showed that:(1) both the Pearson correlation coefficient for the RBF neural network and the root mean squared error were better than the Grey System GM (1, 1) model. They also exhibited a better linear fit and a higher precision of prediction. This paper used Grey Relational Analysis to select the main driving factors; and used the results of linear and nonlinear analysis to build equations for trend extrapolation. In addition, based on the results of principal component analysis, the RBF neural network model appeared to provide a new research area for tourism destination ecological security. One of the key issues was that the tourism ecological security situation of Mount Putuo Island became better, because the index of the RBF model from 2005 to 2014 predicted results from 0.3568 to 0.6475. It appeared that the security level increased the sensitivity level, critical level, and the general level. Additionally, the index of the RBF model from 2015 to 2020 predicted results were from 0.7010 to 0.8135, the security level increased from the relatively safe grade to very safe grade. However, it is well known that the ecological system on the island will be influenced by several factors, including natural, social, and economic, among others. In terms of Mount Putuo Island, during the period of the forecast, it may be affected by typhoons, which may affect the vulnerability of the tourism industry. As such, it may lead to deviation from forecasted results. In short, it is suggested that the perspective of natural ecosystems be considered in future research, which would help to construct a better tourism ecological security index system through better mathematical algorithms to enhance the progress of a RBF neural network model. Consequently, the results could provide critical suggestions to scientifically protect tourism ecological security in Mount Putuo Island. 参考文献 相似文献 引证文献

Trends and forecast of hepatocellular carcinoma in Nantong, China: mortality rates from 1999 to 2011

To investigate the mortality rates of hepatocellular carcinoma (HCC) in Nantong,China from 1999 to 2011, in order to uncover dynamic trends and provide reasoned advice on intervention strategies to decrease HCC incidence and mortality in Nantong in the future. Versions 10 and 9 of the WHO International Classification of Diseases (ICD-10 and ICD-9) were used to determine the number of HCC deaths in Nantong,China for the study's range of years. Thex2 test was applied to compare the HCC mortality rates according to sex and age. The Grey system GM(1,1) model was used to predict the next-5-year HCC mortality for Nantong. Analysis of the standardized mortality in Nantong showed a slight decreasing trend from 1999 to 2011 (x2=57 545.98, P less than 0.001),with males showing a steeper decrease than females. The total mortality of HCC during these years was 53.41 per 100,000 people,with mortality among males being significantly higher than that among females (80.81 per 100,000 people vs. 26.94 per 100,000 people; x2=13 625.42, P less than 0.001). In general, HCC mortality increased with increase in age (general trend:x2=57 545.98, P less than 0.001; male trend: x2=39 878.8, P less than 0.001; female trend: x2=20 105.3, P less than 0.001). However,HCC mortality increased significantly in women after the age of 40 and in men after the age of 35. The GM(1,1) equation was: Yt=-1265.28e(-0.0375t)+1315.5, which predicted that the HCC mortality will decrease to 25.56 per 100,000 people in 2016. Although HCC mortality generally decreased from 1999 to 2011, the rate remained high. Public health intervention strategies may be more effective if they focus on males over the age of 35 and females over the age of 40.

Application of improved artificial neural networks in short-term power load forecasting

Power load forecasting is a key element for power system management and planning. However, it has been proven to be a hard task due to various unstable factors. This paper presents a forecasting methodology based on this particular type of neural network. The scope of this study presents a solution for short-term load forecasting based on a three-stage model which starts with pattern recognition via self-organizing map (SOM), a clustering of the previous partition by K-means algorithm, and finally demand forecasting for each cluster with back propagation neural network (BPNN) improved by additional momentum and variable learning rate methods. The effectiveness of SOM-K-BPNN model has been verified by the final simulation which shows that the proposed model outperforms the BPNN model with default parameters and Grey System GM (1, 1); therefore, empirical results show that the proposed SOM-K-BPNN model is feasible and can fulfil the short-term load forecasting requirements of China.

Impact Factor Dynamic Forecasting Model for Management Science Journals Based on Grey System Theory

A forecast method of the impact factor trend was given based on grey system theory. Using this method, combined with the top 20 management science journals, the grey system GM (1, 1) model was constructed. The model evaluates and predicts the average impact factor trend of the top 20 management science journals.

Prediction of Plastic Injection Shrinkage Ratio Using Grey Theory

The simulation method of the article is based on the analysis of injection molding software MPI and grey system simulation method. The basic model of injection molding parameters are mold temperature, melt temperature and dwell time. So it gets technological parameter of volumetric shrinkage ratio with having been selected point. It comes to the value of simulation with using grey system GM (1, 1) and comparing the value with the measure value. It shows that the volume shrinkage rate which is obtained by using MPI simulation and by using GM (1, 1) grey prediction is consistent and the errors are within 2.2% after comparison. The conclusion is that using grey system GM (1, 1) can effectively predict the volume of injection plastic shrinkage rate and its change trend.

Using a set of GM(1,1) models to predict values of diagnostic symptoms

The main purpose of this study is to develop a methodology of predicting values of vibration symptoms of fan mills in a combined heat and power (CHP) plant. The study was based on grey system theory and GM(1,1) prognostic models with different window sizes for estimating model parameters. Such models have a number of features that are desirable from the point of view of data characteristics collected by the diagnostic system. When using moving window, GM(1,1) models tend to be adaptive. However, selecting an inappropriate window size can result in excessive forecast errors. The present study proposes three possible methods that can be used in automated diagnostic systems to counteract the excessive increase in the forecast error. A comparative analysis of their performance was conducted using data from fan mills in order to select the method which minimises the forecast error.

基于变权-物元分析模型的老工业基地区域生态安全动态预警研究—以吉林省为例

生态安全预警是生态安全研究的重要内容，对维护区域生态安全具有重要的意义。老工业基地区域生态安全预警研究具有一定的特殊性和典型性，选取吉林省为研究区，基于压力、状态、响应（P-S-R）和生态、环境、经济、社会（E-E-E-S）框架模型构建生态安全预警指标体系，运用变权-物元分析模型对1991—2011年吉林省区域生态安全的预警等级进行了测度，并结合灰色系统GM（1，1）预测模型对2015年、2020年区域生态安全态势进行预测预警。研究结果表明：（1）1991--2011年，吉林省生态安全总体水平呈逐步上升的趋势，区域生态安全预警等级从“巨警”上升为“轻警”，指示灯由“红色预警”逐步变为“蓝色预警”；（2）2015年，吉林省的生态安全预警等级属于“轻警”，指示灯为“蓝色预警”，到2020年，吉林省的生态安全预警等级属于“无警”，指示灯为“绿色预警”，但具有向“轻警”变化的态势；（3）制约吉林省生态安全水平提升的主要因素包括单位面积耕地化肥负荷量、城镇化、人均水资源量、GDP增长率、第一产业占GDP比重等，这些因素应是今后生态环境保护调控的重点，本研究为吉林省经济一生态．社会可持续发展提供参考。

Predication Method for China's Civil Aviation Fuel Consumption

With the China’s civil aviation industry gradual market-oriented and the rapid development of China’s economy, China’s civil aviation transportation fuel consumption has grown significantly in nearly past three decades. Therefore, it’s a very important strategic significance of the prediction of China’s civil aviation transportation fuel consumption. In this paper, gray system and neural network approach, combined with China’s civil aviation industry 1980-2010 total traffic volume of the data, we establish gray system GM (1,1) model and BP neural network model for civil aviation transport volume. Training and simulation of the back propagation neutral network model and the gray system GM(1,1) used MATLAB. BP neural network modeling takes into account in three factors: the number of aircraft aviation industry, flight hours and total turnover. The fitting precision of the gray system GM(1,1) model is 64.2% while the fitting precision of the back propagation neutral network model is 90.16%. Thus, the back propagation neutral network model is better for estimating Civil aviation fuel consumption.

Predictive Efficiency Comparison of ARIMA-Time-Series and the Grey System GM(1,1) Forecast Model on Forecasting the Incidence Rate of Hepatitis B

To compare the stochastic autoregressive integrated moving average (ARIMA) model and the grey system GM(1,1) model to predict the hepatitis B incidence in Qianan. Considering the Box-Jenkins modeling and GM(1,1) model approach, hepatitis B incidence was collected monthly from 2004 to 2011, a SARIMA model and a gray system GM(1,1) model were fit. Then, these models were used for calculating hepatitis B incidence for the last 6 observations compared with observed data. The constructed models were performed to predict the monthly incidence rate in 2013. The model SARIMA(0,1,1)(0,1,1)12 and was established finally and the residual sequence was a white noise sequence. Using Excel 2003 to establish the gray system GM(1,1) model of hepatitis B incidence and evaluating the accuracy of the mode as well as forecasting. By posterior-error-test (C=0.435, p=0.821) and residual test, the model accuracy was qualified. It was necessary and practical to apply the approach of ARIMA model in fitting time series to predict hepatitis within a short lead time. The prediction results showed that the hepatitis B incidence in 2013 had a slight upward trend.