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.

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.

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

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.

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.

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.

Dynamic infrared scene simulation using grayscale modulation of digital micro-mirror device

Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by using the digital grayscale modulation method. The infrared image modulation model of a digital micro-mirror device （DMD） is established and then the infrared scene simulator prototype which is based on DMD grayscale modulation is developed. To evaluate its main parameters such as resolution, contrast, minimum temperature difference, gray scale, various DMD subsystems such as signal decoding, image normalization, synchronization drive, pulse width modulation （PWM） and DMD chips are designed. The infrared scene simulator is tested on a certain infrared missile seeker. The test results show preliminarily that the infrared scene simulator has high gray scale, small geometrical distortion and highly resolvable imaging resolution and contrast and yields high-fidelity images, thus being able to meet the requirements for the infrared scene simulation inside a laboratory.

An Inverse Method for Equivalent Gray Gas Radiation Characteristic Parameter

Compared with non-gray model,equivalent gray model has equal calculation accuracy but much higher computing speed.To solve the existing problems of the equivalent gray method,sole ternary model was developed.In the model,coupling solving process of energy balance equations is omitted and the model zone is real closed.Meanwhile,the full furnace temperature and heat flow calculations are avoided,which makes it easier to find the relationship between the equivalent gray gas radiation characteristic parameter and the initial conditions.The radiation characteristic parameter was calculated with different temperature combinations,different model zone sizes and different partial pressures of absorbent gas.The results show the similar variations in the absorption coefficient and emissivity for the equivalent gray model,which both decrease with the increase of the gas temperature and the surface temperature（especially the former one）as well as the model zone size while increase with the increase of the partial pressure of absorbent gas.

京津冀城市韧性的时空演变特征及动态模拟研究

The continuous growth of urban agglomerations in China has increased their complexity as well as vulnerability. In this context, urban resilience is critical for the healthy and sustainable development of urban agglomerations. Focusing on the Beijing-Tianjin-Hebei(BTH) urban agglomeration, this study constructs an urban resilience evaluation system based on four subsystems: economy, society, infrastructure, and ecology. It uses the entropy method to measure the urban resilience of the BTH urban agglomeration from 2000 to 2018.Theil index, standard deviation ellipse, and gray prediction model GM(1,1) methods are used to examine the spatio-temporal evolution and dynamic simulation of urban resilience in this urban agglomeration. Our results show that the comprehensive evaluation index for urban resilience in the BTH urban agglomeration followed a steady upward trend from 2000 to 2018,with an average annual growth rate of 6.72%. There are significant differences in each subsystem’s contribution to urban resilience;overall, economic resilience is the main factor affecting urban resilience, with an average annual growth rate of 8.06%. Spatial differences in urban resilience in the BTH urban agglomeration have decreased from 2000 to 2018, showing the typical characteristic of being greater in the central core area and lower in the surrounding non-core areas. The level of urban resilience in the BTH urban agglomeration is forecast to continue increasing over the next ten years. However, there are still considerable differences between the cities. Policy factors will play a positive role in promoting the resilience level. Based on the evaluation results, corresponding policy recommendations are put forwar to provide scientific data support and a theoretical basis for the resilience construction of the BTH urban agglomeration.