Dimensionality Reduction with Input Training Neural Network and Its Application in Chemical Process Modelling

Many applications of principal component analysis (PCA) can be found in dimensionality reduction. But linear PCA method is not well suitable for nonlinear chemical processes. A new PCA method based on im-proved input training neural network (IT-NN) is proposed for the nonlinear system modelling in this paper. Mo-mentum factor and adaptive learning rate are introduced into learning algorithm to improve the training speed of IT-NN. Contrasting to the auto-associative neural network (ANN), IT-NN has less hidden layers and higher training speed. The effectiveness is illustrated through a comparison of IT-NN with linear PCA and ANN with experiments. Moreover, the IT-NN is combined with RBF neural network (RBF-NN) to model the yields of ethylene and propyl-ene in the naphtha pyrolysis system. From the illustrative example and practical application, IT-NN combined with RBF-NN is an effective method of nonlinear chemical process modelling.

Multimodel-based flight control system reconfiguration control in the presence of input constraints

In this paper,an active fault accommodate strategy is proposed for the plant in the presence of actuator fault and input constraints,which is a combination of a direct adaptive control algorithm with multiple model switching.The μ-modification is introduced in the model reference architecture to construct the adaptive controller.The proof of stability is based on the candidate Lyapunov function,while appropriate switching of multiple models guarantees asymptotic tracking of the system states and the boundedness of all signals.Simulation results illustrate the efficiency of the proposed method.

Global qualitative analysis of new Monod type chemostat model with delayed growth response and pulsed input in polluted environment

In this paper, we consider a new Monod type chemostat model with time delay and impulsive input concentration of the nutrient in a polluted environment. Using the discrete dynamical system determined by the stroboscopic map, we obtain a ＂microorganism-extinction＂ periodic solution. Further, we establish the sufficient conditions for the global attractivity of the microorganism-extinction periodic solution. Using new computational techniques for impulsive and delayed differential equation, we prove that the system is permanent under appropriate conditions. Our results show that time delay is ＂profitless＂.

Construction of Two-Region Input-output Model——A Case Study of Henan Province

On the basis of input-output table of Henan Province and China in 2007, this paper advances a simple method of constructing two-region input-output model using MRIO model, to research the economic link between the industries of Henan Province and the industries of other regions. I summarize the characteristics of this method based on this as follows: when researching inter-regional economic link, the multi-region or two-region input-output model has prominent superiority, and we can conduct preliminary estimation on the multi-region input-output model using location quotient approach.

Environmental input-output model and its analysis with a focus on the solid waste management sectors

An environmental input output model (EIOM) was introduced to the regional solid waste management sectors, which can reflect the direct and indirect relations between the environment and the regional economy development. Some details about how to use the EIOM was discussed. The EIOM was applied to the Changsha City in China. The example results indicate that much useful information related to the environment and the regional economy development can be gained from the solution of the EIOM. Thus, the EIOM can be used as a useful tool for the sustainable development planning including the solid waste management sectors.

The Influences of Energy Price Variation on the Prices of Other Industries: A Study Based on Input-Output Price Model

Energy has laid material foundation for human society during its development. Meanwhile, any change of price in the energy industry may influence social production and people’s life at all levels via an input-output mechanism under which the change related to energy is surely transmitted to other industries. The price change thus incurred in all industries may adversely affect the realization of macroeconomic objective-maintaining prices at a stable level. It is, therefore, needed to conduct an empirical research related to the impact of price change in energy industry on that in other industries. According to the data coming from “China’s 2015 Input-Output Extension Table (42 Departments)” and four hypothetical basis, this article focuses on four energy sectors and analyzes how deeply the price change of them, by use of input-output model, affects that of other industrial products under five conditions where each of their price rises by 10% individually or simultaneously, and why such an influence occurs. The results show that the price rising of the energies in question leads to an upward growth in the prices of other industrial products, especially when their prices go up simultaneously. Besides, the price increase in the four energy sectors doesn’t influence other industries in an accumulation form but actually leads to a rollback in some of other industries. It is recommended to adopt diversified pricing strategies for different energy products, thus maximizing the value of each specific energy, and meanwhile achieving the goals of energy consumption reduction and price equilibrium.

T-Y TUBE MODEL OF HUMAN ASCENDINGAORTIC INPUT IMPEDANCE

This paper proposed a T- Y tube model to simulate foe input impedance of arterial system. It improves and extends the asymmetric T-tube model which was firstproposed by O' Rourke[1] and developed laier by Liu et al.[2]. Based on foe asymmetricT-tube model. a T-Y tube model was proposed by adding branching tubes whichrepresem the iliac arteries.All the tubes are considered to be uniform,viscoelasticlongitudinally tethered cylindrical tubes.The upper tube terminates with a windkesselmodel, while the terminal arterioles of the lowr tube are expressed as a resistance.After proper eraluation of the parameters.the impedance of the arterial system iscalculated under normal physiological and hypertensive condition.The model canpredict impedance in good agreement with the experimentally obtained data no matterin normal physiological condition or in pathological condition In comparison with theasymmeric T-tube model,T- Y tube model is closer to anatomy structure of the human arlerial system and at the sametime much simpler than the extremely complex multiplebranching tube model Therefore it will be a valuable model in studying the influencesof various parameters on aorta impedance and ventricular-vascular coupling.

New model reference adaptive control with input constraints

A new scheme of adaptive control is proposed for a class of linear time-invariant（ LTI） dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. ＂C omposite model reference adaptive control＂of higher performance is seam-lessly combined with ＂positive μ-mod＂,which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.

Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the pre- condition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model.

Nonlinear Systems Identification via an Input-Output Model Based on a Feedforward Neural Network

This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.

Regional Agricultural Input-Output Model and Countermeasure for Production and Income Increase of Farmers in Southern Xinjiang,China

Agricultural input and output status in southern Xinjiang,China is introduced,such as lack of agricultural input,low level of agricultural modernization,excessive fertilizer use,serious damage of environment,shortage of water resources,tremendous pressure on ecological balance,insignificant economic and social benefits of agricultural production in southern Xinjiang,agriculture remaining a weak industry,agricultural economy as the economic subject of southern Xinjiang,and backward economic development of southern Xinjiang.Taking the Aksu area as an example,according to the input and output data in the years 2002-2007,input-output model about regional agriculture of the southern Xinjiang is established by principal component analysis.DPS software is used in the process of solving the model.Then,Eviews software is adopted to revise and test the model in order to analyze and evaluate the economic significance of the results obtained,and to make additional explanations of the relevant model.Since the agricultural economic output is seriously restricted in southern Xinjiang at present,the following countermeasures are put forward,such as adjusting the structure of agricultural land,improving the utilization ratio of land,increasing agricultural input,realizing agricultural modernization,rationally utilizing water resources,maintaining eco-environmental balance,enhancing the awareness of agricultural insurance,minimizing the risk and loss,taking the road of industrialization of characteristic agricultural products,and realizing the transfer of surplus labor force.

Application of Linear Model Predictive Control and Input-Output Linearization to Constrained Control of 3D Cable Robots

Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.

GREY DISPLACEMENT INPUT－OUTPUT MODELS OF MINERAL PROCESSING－METALLURGY SYSTEM

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A Generalization of the Input-Output Pollution Control Model and Product Selection

The input-output pollution control model given in [1] is generalized. The generalization makes it easier for the model to handle many problem instances. A linear program is used to solve the new model. An example is given to show that the new model can handle classes of problems that the original model cannot handle.

基于高通量监测数据的PMF源解析数据输入量研究

为探究数据输入量的变化对源解析结果的影响,以上海某工业区的大气重金属高通量监测数据为例,按不同数据量将监测数据分别输入至正定矩阵因子分解(Positive Matrix Factorization, PMF)模型中,通过考察模型中Q理论值(Qtheo)与Q计算值(Qtrue)的接近程度、源分类以及源贡献与研究区污染源分布特点的吻合情况,分析数据输入量对源解析结果的影响。结果显示:该区域大气重金属污染受工业生产主导(64.44%),其次是扬尘(19.60%)和交通运输(15.96%)。通过对数据量的考察,发现输入量为60~120时能够得出研究区域的污染源数量与贡献率,但考虑到测试成本、获取数据的时间,认为输入量为60~80时,也能得出合理的源解析结果。短期高通量的分钟级数据集,有益于PMF模型输出高精密度、高时效性的源解析结果,是解决应急污染监控的最佳手段。

基于DEA模型的安康市农业投入产出效率评价

为了解安康市现代农业发展效率状况,选取2009—2020年安康市污染治理投资总额、农业固定资产投资额、耕地面积和乡村劳动力资源总数4个农业投入指标,以及农业总产值和农业人均生产值2个农业产出指标,采用数据包络分析(data envelopment analysis,DEA)模型中的BCC模型进行效率分析。结果表明,安康市农业投入产出效率只有2020年的DEA模型是有效的,但从2009年开始,综合效率总体呈现上升趋势;从投入冗余率与产出不足率可以看出,安康市农业总产值基本不存在产出不足的现象,除2020年外,其余各年份在污染治理投资总额、农业固定资产投资额、耕地面积和乡村劳动力资源总数的投入在不同程度都存在冗余,投入结构不合理造成DEA模型无效。

数字经济与实体经济融合是否提升了企业创新能力——基于正反向融合度的非线性检验

促进数字经济与实体经济深度融合,依托数字技术与设备实现核心领域突破性创新,是高质量发展的关键。编制我国非竞争投入产出表,从供需双层面和广义狭义双范畴,可构建并测算我国数字经济与实体经济正、反向融合度,探究数字经济与实体经济融合对实体企业创新影响及内在机制。研究发现,融合度对实体创新的影响存在非线性效应,正向融合度整体提升实体企业创新质量和效率,这与技术吸收能力强化相关;反向融合度处于合理区间时才能拉动创新增长,否则将因成本效应和适应性不足降低实体工业创新质量和效率。

中国高技术产业科技成果转化效率和投入产出结构分析

为进一步探究我国高技术产业中各个行业科技成果转化效率及其投入产出结构,利用2009—2021年的面板数据,采用超效率SBM模型对中国高技术产业科技成果转化效率进行研究,分析中国高技术产业15个行业的科技成果转化综合效率和投入冗余、产出不足,为高技术产业及其行业调整优化投入产出结构、提升科技成果转化效率提供基础。研究发现,中国高技术产业科技成果转化效率呈现出先下降再波动上升的趋势,各行业均呈现波动上升的良好发展趋势,但整体水平不高,行业间差距较大;行业间R&D活动人员、技术改造经费和科技活动经费中的政府资金投入冗余,新产品销售收入产出不足问题突出。基于上述结论提出根据行业特点,先转换再精减冗余人员、重视科研人员再教育、调整资金分配结构、转变政府干预方式、建立健全多渠道合作机制、注重市场需求导向促进理论成果市场化等建议,以进一步提升高技术产业科技成果转化效率。

“双碳”背景下中国制造业绿色出口竞争力研究

在“双碳”背景下,提升中国制造业绿色出口竞争力对发展绿色贸易具有重要意义。论文引入碳排放权交易价格,运用多区域投入产出模型,将传统的单位劳动成本改进为单位绿色隐含劳动成本,将出口增加值国际市场份额改进为绿色出口增加值国际市场份额,进而构建绿色出口竞争力指数,测算并比较中国十大制造行业绿色出口竞争力。研究发现,2005—2019年中国大部分制造行业单位绿色隐含劳动成本和绿色出口竞争力指数均在上升,其中单位绿色隐含劳动成本上升最多的是金属制品业,从2005年的0.409上升到2019年的0.780,绿色出口竞争力指数上升最多的是非金属矿物制品业,从0.243上升到1.069。回归结果表明,研发投入和行业规模对中国制造业绿色出口竞争力有显著正向影响。针对以上结论,在“双碳”目标下,论文提出提高劳动生产率、培育可持续竞争优势、加大技术研发投入等政策建议。