Application of Gray Metabolic Model in the Prediction of the Cotton Output in China

In order to forecast the cotton output of China in the year 2011, Gray Metabolic Forecast Model is established based on both the Gray Forecast Model and the Metabolic Theory. According to the actual situation, forecast results of conventional GM (1, 1) Model and Metabolism GM (1, 1) Model are analyzed, showing that Metabolic Forecast Model has higher precision than the conventional forecast model. Therefore, Metabolism GM (1, 1) Model is used to forecast the cotton output of China in the year 2011, which is 614 968.3 thousand tons.

Prediction of the amount of urban waste solids by applying a gray theoretical model

Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in China than others, especially for urban waste solids. Most of the design works up to now are based on a roughly estimation of the amount of urban waste solids without any theoretical support, which lead to a series problems. To meet the basic information requirements for the design work, the amount of the urban waste solids was predicted in this research by applying the gray theoretical model GM (1,1) through non linear differential equation simulation. The model parameters were estimated with the least square method (LSM) by running a certain MATALAB program, and the hypothesis test results show that the residual between the prediction value and the actual value approximately comply with the normal distribution N (0,0 21 2), and the probability of the residual within the range (-0 17, 0 19) is more than 95%, which indicate obviously that the model can be well used for the prediction of the amount of waste solids and those had been already testified by the latest two years data about the urban waste solids from Loudi City of China. With this model, the predicted amount of the waste solids produced in Loudi City in the next 30 years is 8049000 ton in total.

Gray Model of Human Body Shape

In order to determine the control dimensions of human body in pattern construction and provide the basis for size specification in clothing industry, a gray model is described and established in the application of predicting size specification. By comparing the features of gray model and regression model, it is proved that the former has many advantages over the latter, i.e. more practical and more effective in this application. So it is strongly suggested to apply the innovative gray model instead of the traditional regression model to facilitate the calculation procedure in pattern construction.

Application of Renewal Gray GM (1,1) Model to Prediction of Landslide Deformation

The gray renewal GM (1,1) landslide prediction model was established by improving the gray model. Based on the established model, the author has made prediction of landslide deformation to the Xiangjiapo landslide and the Lianziya dangerous rock body. The results show that the gray renewal GM (1,1) model can supplement the new information in time and remove the old information which reduces the meaning of the information because of time lapse. Therefore, the model is closer to reality.

Study on soil erosion dynamics in typical regionof southern China based on remote sensing, GISand gray forecast model

This paper StUdies soil erosion dynamics in the typical region of southem China based onremote sensing, GIS tecndques and gray forecast model. The resultS of survey on Xingguo countyshown the soil eroded area and annual soil erosion amount decreased by 19.09% and 43.05%reSPectively from 1958 to 1988. The results of gray forecast model presented that soil eroded areaincreased from 818.04 km2 in 1988 to 1276.69 km2 in 1995. in the meanthne the total soil erosiollamount decreased from 607.21×104 ba in 1988 to 472. 12 ×104 t/a in 1995. By comparing differentlanduse types, the soil loss modulus of the forest was the lowest with 177. 16~187.75t/km2. a, on thecontraly the bare land was the highest with 10626.76~11265.48 t/km2. a. so the high vegetationcoverage can decrease soil and water loss effectively.

Application of Gray Metabolic GM (1,1) Model in Prediction of Annual Total Yields of Chinese Aquatic Products

To predict the annual total yields of Chinese aquatic products in future five years ( 2011-2015) ,based on the theory and method of gray system,this paper firstly establishes a conventional GM ( 1,1) model and a gray metabolic GM ( 1,1) model respectively to predict the annual total yields of Chinese aquatic products in 2006-2009 and compare the prediction accuracy between these two models. Then,it selects the model with higher accuracy to predict the annual total yields of Chinese aquatic products in future five years. The comparison indicates that gray metabolic GM ( 1,1) model has higher prediction accuracy and smaller error,thus it is more suitable for prediction of annual total yields of aquatic products. Therefore,it adopts the gray metabolic GM ( 1,1) model to predict annual total yields of Chinese aquatic products in 2011-2015. The prediction results of annual total yields are 55. 32,57. 46,59. 72,62. 02 and 64. 43 million tons respectively in future five years with annual average increase rate of about 3. 7% ,much higher than the objective of 2. 2% specified in the Twelfth Five-Year Plan of the National Fishery Development ( 2011 to 2015) . The results of this research show that the gray metabolic GM ( 1,1) model is suitable for prediction of yields of aquatic products and the total yields of Chinese aquatic products in 2011-2015 will totally be able to realize the objective of the Twelfth Five-Year Plan.

Lijiang Tourism Prediction Based on the Gray Dynamic GM Model and Computer Simulation

[Objective] Taken the Linjiang tourism as an example, tourism forecast system was established, difficulties related to the work of tourist area were solved. [Method] Dynamic predicted response model of Lijiang tourism market was established, through the gray correlation model GM (1, 1) and time-series method, using a computer simulation program for the actual model of operation, Lijiang tourism prospects were predicted and predicting results were evaluated. [Result] Total revenue of model gray parameter of Lijiang tourism a= 0.572 3 from 2009 to 2011, internal control parameters u=0.393 7, x(t+1) =-0.563 3exp(-0.572 3t)+0.688 0; total reception numbers of model gray parameter of Lijiang tourism a = 0.125 6, internal control parameters u = 344. 326 0, x(t+1)=3 102.483 5 exp(0.125 6 t)-2 741.283 5. Test results of two models showed that fitting degrees were good, and at the same time predicted that total revenue of Lijiang tourism reached 13 000 000 000, and total reception numbers reached 8 800 000. [Conclusion] This predicted system can carry out precision forecast for other tourist areas when cannot get all the information.

Gray Connection Analysis on Grain Yield and Agricultural Fundamental Infrastructure

Although the agriculture in Heilongjiang Province has develope poor historical basis and differences between rural and urban institutional fa d ct effectively in recent years, due to issues such as ors, the backward of the agricultural fundamental infrastructure is always the major obstacle in rural economic development of Heilongjiang Province, which prevents the advantage of agricultural production from being fully developed, leading to the increase rate of the grain yield to grow slowly. The backward reflects in the following aspects, the serious aging of water facilities, insufficient agricultural machinery and equipment, low leve of rural roads, lacking of research equipment, shortage of ecological protection facilities, and so on. Based on the latcr data of Heilongjiang Province, this paper analyzed the connection between agricultural fundamental infrastructure and grain yield by using the gray connected model, differentiated primary rural fundamental infrastructure from the secondary one, and provided some suggestions to develop rural areas

Determination on Microclimatic Conditions at Vines upon Development on Gray Mold (<i>Botrytis cinerea</i>)

One of the most important plant diseases in viticulture is gray mold caused by Botrytis cinerea Pers. Fr., the anamorph of an ascomycete fungus (Botryotinia fuckeliana Whetzel). Locality Smilica, Kavadarci, Republic of North Macedonia, was the place where experimental fields with white varieties Smedervka and Zilavka were continuously observed. Working hypothesis was to follow development of the disease after increasing glucose over 11% until the time of the grape harvest, and microclimate was monitored at the same time. In both white varieties Smederevka and Zilavka on the control variants weren’t used botricide treatments to distinguish between the variants that were conventionally treated against B. cinerea. The aim of the research was to determine how microclimatic conditions affect the development of B. cinerea and consequently to create forecasting model for gray mold. The forecasting model for B. cinerea is based on relationship between temperature and humidity in the vines’ canopies. The aim of the research is to prevent development of B. cinerea and consequently reduce the number of chemical treatments.

Identification of key genes and active anti-inflammatory ingredients in Panax medicinal plants by climate-regulated callus culture combined with gene-component-efficacy gray correlation analysis

Objective:We aimed to establish a novel strategy for identifying key genes and active anti-inflammatory ingredients in Panax medicinal plants.Methods:First,fresh roots of 2-year-old Panax plants,including P.ginseng C.A.Mey.,P.quinquefolium L.,P.notoginseng(Burk.)F.H.Chen,P.japonicus C.A.Mey.,P.japonicus Mey.var.major(Burk.)C.Y.Wu et K.M.Feng,were selected as explants,and callus formation was induced under three experimental temperatures(17,24,and 30℃).Second,high-performance liquid chromatography-mass spectrometry was used to analyze the saponin content of the callus.Nitric oxide reduction efficacy was used for“component-efficacy”gray correlation analysis to find the active anti-inflammatory ingredients.Quantitative reverse-transcription polymerase chain reaction(qRT-PCR)was used to determine the inflammatory factors and verify the active ingredients’anti-inflammatory effects.Finally,qRT-PCR was used to detect the expression of key genes in the callus,and“gene-component”gray correlation analysis was used to examine the relationships between the regulatory pathway of the genes and the components.Results:Among the three experimental temperatures(17,24,and 30℃),the lowest temperature(17℃)is the most suitable for generating Panax callus.Lower-latitude native Panax notoginseng is more adaptable under high culture temperatures(24℃and 30℃)than other Panax plants.The ginsenoside contents of the callus of P.notoginseng and P.japonicus were the highest under similar climate conditions(17℃).Major anti-inflammatory components were G-Rh1,G-Rb1,G-Rg3,and G-Rh6/FloralGKa.CYP76A47 contributed to the accumulation of anti-inflammatory components.Conclusions:This study provides a strategy for the gene-component-efficacy correlational study of multi-component,multi-functional,and multi-purpose plants of the same genus.

A Correlation Analysis of Tourism Based on Gray Theory——A case of Xingwen County

Tourism industry has already become an important part of national economy,which not only played a positive role in the development of the economy,but promoted the adjustment and optimization of industrial structure.The paper analyzes the correlation between the tourism industry and the other industry through changes of the Xingwen County tourism industrial output value in the past seven years.With the Gray Model,the correlation degree among the tourism industry and agriculture,industry,transport,wholesale and retail trade,postal and telecommunications industries is measured.The analysis result indicates that the order of the corresponding correlation degree:catering accommodation is 0.691> wholesale and retail is 0.617 > agriculture is 0.616 > Postal and telecommunications industry is 0.610> Transport is 0.602> Industry is 0.537.In accordance with the actual conditions of the industry in Xingwen,the industrial development policies and measures are put forward,which help the tourism industry Xingwen their rapid,coordinated and highly efficient operation.

X-ray Microtomography of the Carbonation Front Shape Evolution of Cement Mortar and Modeling of Accelerated Carbonation Reaction

In situ monitoring of the microstructure evolution of cement mortar in accelerated carbonation reaction for different carbonation ages was carried out by X-ray computed tomography （XCT）. And the carbonation degrees of different time were measured by the volume fraction of uncarbonated and carbonated parts. Meanwhile, we presented a model for the carbonation of cement mortar by means of X-ray computed tomography （XCT）. Based on the principles of chemical engineering processes, the reacted products become a solid inert ash layer. Finally, the model was validated with results of accelerated carbonation of cement mortar. The model is thus able to reasonably predict the carbonation ohenomena for accelerated conditions.

Comprehensive Evaluation Model of Reservoir Operation Based on Improved Set Pair Analysis

A comprehensive evaluation model based on improved set pair analysis is established. Considering the complexity in decision-making process, the model combines the certainties and uncertainties in the schemes, i.e., identical degree, different degree and opposite degree. The relations among different schemes are studied, and the traditional way of solving uncertainty problem is improved. By using the gray correlation to determine the difference degree, the problem of less evaluation indexes and inapparent linear relationship is solved. The difference between the evaluation parameters is smaller in both the fuzzy comprehensive evaluation model and fuzzy matter-element method, and the dipartite degree of the evaluation result is unobvious. However, the difference between each integrated connection degree is distinct in the improved set pair analysis. Results show that the proposed method is feasible and it obtains better effects than the fuzzy comprehensive evaluation method and fuzzy matter-element method.

Application of Grey Model and Neural Network in Financial Revenue Forecast

There are many influencing factors of fiscal revenue,and traditional forecasting methods cannot handle the feature dimensions well,which leads to serious over-fitting of the forecast results and unable to make a good estimate of the true future trend.The grey neural network model fused with Lasso regression is a comprehensive prediction model that combines the grey prediction model and the BP neural network model after dimensionality reduction using Lasso.It can reduce the dimensionality of the original data,make separate predictions for each explanatory variable,and then use neural networks to make multivariate predictions,thereby making up for the shortcomings of traditional methods of insufficient prediction accuracy.In this paper,we took the financial revenue data of China’s Hunan Province from 2005 to 2019 as the object of analysis.Firstly,we used Lasso regression to reduce the dimensionality of the data.Because the grey prediction model has the excellent predictive performance for small data volumes,then we chose the grey prediction model to obtain the predicted values of all explanatory variables in 2020,2021 by using the data of 2005–2019.Finally,considering that fiscal revenue is affected by many factors,we applied the BP neural network,which has a good effect on multiple inputs,to make the final forecast of fiscal revenue.The experimental results show that the combined model has a good effect in financial revenue forecasting.

Intelligent predictive model of ventilating capacity of imperial smelt furnace

In order to know the ventilating capacity of imperial smelt furnace(ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.

A generalized model of TiOx-based memristive devices and its application for image processing

Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly favorable for the realization of its circuits and applications. In this paper, we propose a novel memristive model of TiOx-based devices, which considers the negative differential resistance（NDR） behavior. This model is physics-oriented and passes Linn＇s criteria. It not only exhibits sufficient accuracy（IV characteristics within 1.5% RMS）, lower latency（below half the VTEAM model）,and preferable generality compared to previous models, but also yields more precise predictions of long-term potentiation/depression（LTP/LTD）. Finally, novel methods based on memristive models are proposed for gray sketching and edge detection applications. These methods avoid complex nonlinear functions required by their original counterparts. When the proposed model is utilized in these methods, they achieve increased contrast ratio and accuracy（for gray sketching and edge detection, respectively） compared to the Simmons model. Our results suggest a memristor-based network is a promising candidate to tackle the existing inefficiencies in traditional image processing methods.

A Hybrid Model for the Mid-Long Term Runoff Forecasting by Evolutionary Computation Techniques

The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology forecasting ones. The observed data is divided into two parts; the slow 'smooth and steady' data, and the fast 'coarse and fluctuation' data. Under the divide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in the northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM).

Prediction of a maximum pull-out load of anchor bolts using an optimal combination model

The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.

Evaluation and prediction of earth pressure balance shield performance in complex rock strata:A case study in Dalian,China

This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.