A Study on an Extensive Hierarchical Model for Demand Forecasting of Automobile Components

Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.

A parameterization scheme of vertical mixing due to inertial internal wave breaking in the ocean general circulation model

Based on the theoretical spectral model of inertial internal wave breaking （fine structure） proposed previ- ously, in which the effects of the horizontal Coriolis frequency component f-tilde on a potential isopycnal are taken into account, a parameterization scheme of vertical mixing in the stably stratified interior be- low the surface mixed layer in the ocean general circulation model （OGCM） is put forward preliminarily in this paper. Besides turbulence, the impact of sub-mesoscale oceanic processes （including inertial internal wave breaking product） on oceanic interior mixing is emphasized. We suggest that adding the inertial inter- hal wave breaking mixing scheme （F-scheme for short） put forward in this paper to the turbulence mixing scheme of Canuto et al. （T-scheme for short） in the OGCM, except the region from 15°S to 15°N. The numeri- cal results ofF-scheme by usingWOA09 data and an OGCM （LICOM, LASG/IAP climate system ocean model） over the global ocean are given. A notable improvement in the simulation of salinity and temperature over the global ocean is attained by using T-scheme adding F-scheme, especially in the mid- and high-latitude regions in the simulation of the intermediate water and deep water. We conjecture that the inertial internal wave breaking mixing and inertial forcing of wind might be one of important mechanisms maintaining the ventilation process. The modeling strength of the Atlantic meridional overturning circulation （AMOC） by using T-scheme adding F-scheme may be more reasonable than that by using T-scheme alone, though the physical processes need to be further studied, and the overflow parameterization needs to be incorporated. A shortcoming in F-scheme is that in this paper the error of simulated salinity and temperature by using T-scheme adding F-scheme is larger than that by using T-scheme alone in the subsurface layer.

Application of synthetic principal component analysis model to mine area farmland heavy metal pollution assessment

Referring to GB5618-1995 about heavy metal pollution,and using statistical analysis SPSS,the major pollutants of mine area farmland heavy metal pollution were identified by variable clustering analysis.Assessment and classification were done to the mine area farmland heavy metal pollution situation by synthetic principal components analysis (PCA).The results show that variable clustering analysis is efficient to identify the principal components of mine area farmland heavy metal pollution.Sort and clustering were done to the synthetic principal components scores of soil sample,which is given by synthetic principal components analysis.Data structure of soil heavy metal contaminations relationships and pollution level of different soil samples are discovered.The results of mine area farmland heavy metal pollution quality assessed and classified with synthetic component scores reflect the influence of both the major and compound heavy metal pol- lutants.Identification and assessment results of mine area farmland heavy metal pollution can provide reference and guide to propose control measures of mine area farmland heavy metal pollution and focus on the key treatment region.

Influences of affiliated components and train length on the train wind

The induced airfl w from passing trains,which is recognized as train wind,usually has adverse impacts on people in the surroundings,i.e.,the aerodynamic forces generated by a high-speed train＇s wind may act on the human body and endanger the safety of pedestrians or roadside workers.In this paper,an improved delayed detached eddy simulation（IDDES） method is used to study train wind.The effects of the affiliate components and train length on train wind are analyzed.The results indicate that the aff liated components and train length have no effect on train wind in the area in front of the leading nose.In the downstream and wake regions,the longitudinal train wind becomes stronger as the length of the train increases,while the transverse train wind is not affected.The presence of affiliate components strengthens the train wind in the near fiel of the train because of strong fl w solid interactions but has limited effects on train wind in the far field.

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

A COM-based Framework for Management,Analysis and Visualization of Large Scope Digital Elevation Models

This paper presents a component object model (COM) based framework for managing, analyzing and visualizing massive multi-scale digital elevation models (DEMs). The framework consists of a data management component (DMC), which is based on RDBMS/ORDBMS, a data analysis component (DAC) and a data render component (DRC). DMC can manage massive multi-scale data expressed at various reference frames within a pyramid database and can support fast access to data at variable resolution. DAC integrates many useful applied analytic functions whose results can be overlaid with the 3D scene rendered by DRC. DRC provides view-dependent data paging with the support of the underlying DMC and organizes the potential visible data at different levels into rendering.

Modelling the Sorption of 63Ni to Granitic Materials： Application of the Component Additive Model

The component additive modelling approach is based on summing the results from models already calibrated with pure mineral phases. The summation can occur as the sum of results for thermodynamic surface speciation models or as the sum of pseudo-thermodynamic models for adsorption on individual mineral phases. Static batch sorption experiments of 63Ni are with different granitic rocks and component minerals. XRD analyses have been used to calculate the percentage mineralogical composition of the granitic rocks. Sorption data has been modelled using non electrostatic correction models to obtain Rdfor the granitic rocks and mineral. Ra values for the granitic rocks predicted from the component additive model have been compared to experimental values. Results showed that predicted Rd values for granite adamellite, biotite granite and rapakivi granite were identical to the experimentally determined values, whereas, for graphic granite and grey Granite, the predicted and experimentally determined Ra values were much different. The results also showed a greater contribution to the bulk Raby feldspar while quartz showed the least contribution to the Rd.

Structural Analysis and Design of Steel Connections Using Component-Based Finite Element Model

This paper introduces CBFEM （component-based finite element model） which is a new method to analyze and design connections of steel structures. Design focused CM （component model） is compared to FEM （finite elements models）. Procedure for composition of a model based on usual production process is used in CBFEM. Its results are compared to those obtained by component method for portal frame eaves moment connection with good agreement. Design of moment resistant column base is demonstrated by a case loaded by two directional bending moments and normal force. Interaction of several connections in one complex joint is explained in the last example. This paper aims to provide structural engineers with a new tool to effectively analyze and design various joints of steel structures.

Rapid prediction of floating and sinking components of raw coal

A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.

Component modeling and updating method of integrated energy systems based on knowledge distillation

Amid the backdrop of carbon neutrality, traditional energy production is transitioning towards integrated energy systems (IES), where model-based scheduling is key in scenarios with multiple uncertainties on both supply and demand sides. The development of artificial intelligence algorithms, has resolved issues related to model accuracy. However, under conditions of high proportion renewable energy integration, component load adjustments require increased flexibility, so the mathematical model of the component must adapt to constantly changing operating conditions. Therefore, the identification of operating condition changes and rapid model updating are pressing issues. This study proposes a modeling and updating method for IES components based on knowledge distillation. The core of this modeling method is the light weighting of the model, which is achieved through a knowledge distillation method, using a teacher-student mode to compress complex neural network models. The triggering of model updates is achieved through principal component analysis. The study also analyzes the impact of model errors caused by delayed model updates on the overall scheduling of IES. Case studies are conducted on critical components in IES, including coal-fired boilers and turbines. The results show that the time consumption for model updating is reduced by 76.67 % using the proposed method. Under changing conditions, compared with two traditional models, the average deviation of this method is reduced by 12.61 % and 3.49 %, respectively, thereby improving the model's adaptability. The necessity of updating the component model is further analyzed, as a 1.00 % mean squared error in the component model may lead to a power deviation of 0.075 MW. This method provides real-time, adaptable support for IES data modeling and updates.

Catalytic Hydrothermal Liquefaction of Algae for Production of Bio-oil with Solid Superacid Catalyst SO_(4)^(2−)/ZrO_(2)

Solid superacid SO_(4)^(2−)/ZrO_(2)as heterogeneous catalyst was prepared to upgrade the bio-oil in the progress of hydrother-mal liquefaction(HTL)for the represented algae of Chlorella vulgaris and Enteromorpha prolifera.The solid superacid catalyst could obviously adjust the composition of the bio-oil and improve the higher heating values(HHVs).The catalytic performance could be regulated by adjusting the acid amount and acid strength of SO_(4)^(2−)/ZrO_(2).Furthermore,it was explored the catalytic effects of SO_(4)^(2−)/ZrO_(2)by the HTL for algae major model components,including polysaccharides,proteins,lipids,binary mixture and ternary mixture.The results showed that the introducing of SO_(4)^(2−)/ZrO_(2)catalyst could increase the yields of bio-oil from proteins and lipids,and avoid the Maillard reaction between polysaccharides and proteins.Moreover,a possible reaction pathway and mechanisms has proposed for the formation of bio-oils from HTL of algae catalyzed by SO_(4)^(2−)/ZrO_(2)based on the systematic research of the producing bio-oil from major model components.

A Brief Introduction to BNU-HESM1.0 and Its Earth Surface Temperature Simulations

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human--earth system model, BNU- HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO2 concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO2 concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM 1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate.

Analysis and Design of Soils and Terrain Digital Database (SOTER) Management System Based on Object-Oriented Method

A SOTER management system was developed by analyzing, designing, programming, testing, repeated proceeding and progressing based on the object-oriented method. The function of the attribute database management is inherited and expanded in the new system. The integrity and security of the SOTER database are enhanced. The attribute database management, the spatial database management and the model base are integrated into SOTER based on the component object model (COM), and the graphical user interface (GUI) for Windows is used to interact with clients, thus being easy to create and maintain the SOTER, and convenient to promote the quantification and automation of soil information application.

HYSYS Automation and Its Application on Evaluation of Plate Heat Exchanger

When simulating or designing plate heat exchangers for multicomponent mixtures, most designers are often perplexed with the question on how to choose or estimate the physical property param- eters and hope to have a reliable database that could be adopted. The commercial codes HYSYS supply the physical property package on over 1500 pure substances and over 16 000 binary coefficients for them. This work has briefly presented an efficient communication interface based on the Microsoft Component Object Model （COM） between inner plate heat exchanger simulation codes and the HYSYS package. The application of a custom-made HYSYS-COM interface has shown high efficiency, such as significant reduction of time needed for evaluating each process stream＇s properties. This automation method can be conveniently extended to further optimization study for any specific operation device such as heat transfers, columns, and other facilities.

Computational implementation of a GIS developed tool for prediction of dynamic ground movement and deformation due to underground extraction sequence

In the last century, there has been a significant development in the evaluation of methods to predict ground movement due to underground extraction. Some remarkable developments in three-dimensional computational methods have been supported in civil engineering, subsidence engineering and mining engineering practice. However, ground movement problem due to mining extraction sequence is effectively four dimensional （4D）. A rational prediction is getting more and more important for long-term underground mining planning. Hence, computer-based analytical methods that realistically simulate spatially distributed time-dependent ground movement process are needed for the reliable long-term underground mining planning to minimize the surface environmental damages. In this research, a new computational system is developed to simulate four-dimensional （4D） ground movement by combining a stochastic medium theory, Knothe time-delay model and geographic information system （GIS） technology. All the calculations are implemented by a computational program, in which the components of GIS are used to fulfill the spatial-temporal analysis model. In this paper a tight coupling strategy based on component object model of GIS technology is used to overcome the problems of complex three-dimensional extraction model and spatial data integration. Moreover, the implementation of computational of the interfaces of the developed tool is described. The GIS based developed tool is validated by two study cases. The developed computational tool and models are achieved within the GIS system so the effective and efficient calculation methodology can be obtained, so the simulation problems of 4D ground movement due to underground mining extraction sequence can be solved by implementation of the developed tool in GIS.

An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes

A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.

Research of whispered speech vocal tract system conversion based on universal background model and effective Gaussian components

Directing to the weakness of the present fixed values mapping methods （method_F）, a vocal tract system conversion method based on the universal background model （UBM） is proposed for improving the performance of the speech conversion system from Chinese whis- pered speech to normal speech. For the numerous components of UBM, the errors produced by the acoustical probability density statistical model can＇t be ignored. Thus an effective Gaus- sian mixture components chosen method based on the posterior probability summation of the minimum spectral distortion is developed to optimizing the system performance. The proposed method （method_U） is analyzed and compared using the performance index （PI） based on Itakura-Saito spectral distortion measure. It is shown experimentally that the performance of method_U is more stability for different speakers and different phonemes than that of method_F. The average PI of method_U is better than method_F. It is shown that by selecting effective Gaussian mixture components, the PI of method_U can be further improved 5.11%. Subjective auditory tests also show that the proposed method can improve the definition and intelligibility of conversion speech.

ON ASYMPTOTIC JOINT DISTRIBUTIONS OF EIGENVALUES OF RANDOM MATRICES WHICH ARISE FROM COMPONENTS OF COVARIANCE MODEL

In this paper, the authors derive the asymptotic joint distributions of theeigenvalues of some random matrices which arise from components of covariance model.

Research of MMW radiometer virtual prototyping technology

The idea of millimeter-wave (MMW) radiometer virtual prototyping is discussed in this paper. Designing environment, designing method and the main modeling components of virtual MMW radiometer are researched. Important external parameters, which have significant influence to composing system, are used to components modeling, and then components are taken to buildup virtual MMW radiometer system. Moreover, the effect to output is contrasted whether there is a low-noise amplifier or not.

Analysis of the Framework of Microsoft DNA

Microsoft DNA(Distributed interNet Application) has p rovided a effective framework of combination PC with the Internet perfectly; In addition, this open framework hase also given the integration of multilingual co mponents a strong managing platform. This article has deeply analysed the main technologys of Microsoft DNA, involve COM basic technology, framework of DNA, Microfost UDA(Universal Data Access),com ponent management with COM+, asynchronous communication with MSMQ(M icrosoft Message Queue). In addition, based on a comparative analysise with the C/S(Client/Server) framework, the author has illustrated the excellency of the Multi-tier framework of Microsoft DNA.