Model for Bidding and Tendering with Bill of Quantities Based on Bid-Winning Estimate at Reasonable Low Price

The possibility and rationality of introducing an bid-winning estimate based on a reasonable low price into construction bidding mode with bill of quantities were analyzed by setting up a model for bidding and tendering, and the functions of the estimate of reasonable low price in the bidding were revealed. On this basis, a new bidding mode of the project with bill of quantities was pro- posed. The application of the new mode will be advantageous to the promotion of the bill of quantities in China.

Analysis and Evaluation of Housing Price Factors Using Mathematical Modeling

In recent years,the real estate industry has achieved significant progress,driving the development of related sectors and playing a crucial role in economic growth.However,rapid real estate market expansion has led to challenges,particularly concerning housing prices,which have drawn widespread societal attention.This article explores the theories of housing prices,analyzes factors influencing them,and conducts an empirical investigation of the impact of representative factors on ordinary residential prices.Using regression analysis and the entropy weight method,a mathematical model was developed to examine how various factors affect housing prices.

Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning

With the continuous development of artificial intelligence technology,its application field has gradually expanded.To further apply the deep reinforcement learning technology to the field of dynamic pricing,we build an intelligent dynamic pricing system,introduce the reinforcement learning technology related to dynamic pricing,and introduce existing research on the number of suppliers(single supplier and multiple suppliers),environmental models,and selection algorithms.A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions.The first step is to analyze the pricing strategies of e-commerce platforms in mature markets,analyze the optimal pricing and profits of various enterprises under different strategy combinations,compare different market equilibriums and solve the Nash equilibrium.Then,assuming that all consumers are naive in the market,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations,the subgame refined Nash equilibrium is solved.Finally,assuming that the market includes all experienced consumers,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.

Pricing Game Model of Wasted Clothing Recycling and Remanufacturing Based on Government Subsidy

In the global environment of pursuing resource regeneration and green environmental protection, more and more wasted clothing need to be solved. In order to make full use of the wasted clothing and save land and soil resources, an idea of wasted clothing's recycling and remanufacturing is put forward. In the new idea a pricing game model is established basing on Stacklberg differential game theory between traditional and remanufactured clothing. In this model, the differences in consumers' willingness to pay and the government's subsidies are considered. Government's optimal subsidy are obtained which ensure not only the interests of manufacturers but also environmental reputation and maximum social benefits. The study is helpful to push the wasted clothing's recycling and remanufacturing plan. It makes some index more precise quantification as government's subsidy, manufacturers and the social benefits. Government and manufactures can make the detailed cooperation plan reference to it.

Pricing Model of Multiattribute Derivatives Based on Mixed Process

By Analyzing the behavior and character of derivative security, the authors established a pricing model of multiattribute derivative security whose underlying asset pricing process is a mixed process, and obtained a new model for option pricing of multiattribute derivatives based on mixed process, and improved some original results.

Research on the Protection of Vulnerable Groups in Water Pollution Conflicts Based on Binomial Tree Pricing Model

The interests of vulnerable groups can’t be guaranteed due to their weaker capacity and the limited interests demand channels during the water pollution conflicts. The interest protection for the vulnerable people in the water pollution conflicts has attracted attentions of the international scholars. The paper tries to construct the market mechanism which can make the vulnerable people to involve in the emission trading. The vulnerable people can buy American put option in the emission trading market. When the price of the emission runs below the contract price, the vulnerable people can get the benefit through executing the option. When the price of the emission runs above the contract price, the vulnerable people can give up the right. The binomial tree option pricing model can help the vulnerable people to make a decision through the analysis of the worth of the American put option.

Application of Binomial Option Pricing Model to the Appraisal of Knowledge Management Investment

This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.

Cost Management Strategy of Highway Engineering Construction Stage Using the List Pricing Model

Highway engineering requires higher investment and requires a long time of management compared to other construction projects.There are many factors that affect the project cost during the engineering construction stage of a highway.The effective development of cost management in the construction phase of highway engineering under the list pricing model can avoid unnecessary waste and help control the cost of highway engineering.However,there are still some problems in the development of cost management in the construction phase of highway engineering,which will affect the role of the list-based pricing mode in cost management.This paper explores and analyzes the advantages of the list pricing model and the problems existing in the cost management of the highway engineering construction stage under the list pricing model,and proposes effective management strategies to improve cost management of the highway engineering construction stage.

Research on Construction of Bill of Quantities of Prefabricated Buildings Based on BIM

Building Information Model(BIM)Technology can be widely used in various construction fields.The construction quality and project cost of the prefabricated construction industry based on BIM can be effectively controlled.Based on BIM Technology,the integration of bill of quantities can effectively control the cost of prefabricated construction and improve competitiveness in the bidding process.Based on this,the characteristics and advantages of bill of quantities pricing based on BIM were expounded in this paper.Besides,the structure and content construction of bill of quantities were analyzed,followed by an analysis of pricing control strategy based on BIM were analyzed for assembly building quantities for reference.

ON INFORMATION THEORY METHOD FOR RELIABILITY ASSESSMENT OF SYSTEMS CONSISTING OF DIFFERENT SUCCESS FAILURE MODEL UNITS

Using the characteristic of addition of information quantity and the principle of equivalence of information quantity, this paper derives the general conversion formulae of the formation theory method conversion (synthesis) on the systems consisting of different success failure model units. According to the fundamental method of the unit reliability assessment, the general models of system reliability approximate lower limits are given. Finally, this paper analyses the application of the assessment method by examples, the assessment results are neither conservative nor radical and very satisfactory. The assessment method can be popularized to the systems which have fixed reliability structural models.

Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost

Stock price forecasting is an important issue and interesting topic in financial markets.Because reasonable and accurate forecasts have the potential to generate high economic benefits,many researchers have been involved in the study of stock price forecasts.In this paper,the DWT-ARIMAGSXGB hybrid model is proposed.Firstly,the discrete wavelet transform is used to split the data set into approximation and error parts.Then the ARIMA(0,1,1),ARIMA(1,1,0),ARIMA(2,1,1)and ARIMA(3,1,0)models respectively process approximate partial data and the improved xgboost model(GSXGB)handles error partial data.Finally,the prediction results are combined using wavelet reconstruction.According to the experimental comparison of 10 stock data sets,it is found that the errors of DWT-ARIMA-GSXGB model are less than the four prediction models of ARIMA,XGBoost,GSXGB and DWT-ARIMA-XGBoost.The simulation results show that the DWT-ARIMA-GSXGB stock price prediction model has good approximation ability and generalization ability,and can fit the stock index opening price well.And the proposed model is considered to greatly improve the predictive performance of a single ARIMA model or a single XGBoost model in predicting stock prices.

Carbon emission scenarios of China's power sector:Impact of controlling measures and carbon pricing mechanism

The study constructs a low-carbon path analysis model of China's power sector based on TIMES model and presents a comparative analysis of carbon emissions under Reference,Low-Carbon and Enhanced Low-Carbon scenarios,and the main difference of the three scenarios is manifested by policy selection and policy strength.The conclusions are drawn as follows:(1)The peak of carbon emission in China's power sector will range from 4.0 GtCO2 to 4.8 GtCO2,which implies an increment of 0.5e1.3 billion or 14%e35%from the 2015 levels.(2)Introducing carbon price is an effective way to inhibit coal power and promote non-fossil fuels and Carbon Capture,Utilization and Storage applications(CCUS).The carbon emission reduction effects will gradually increase with carbon price.When the carbon price attains to CN￥150 t
1CO2,the CO2 emission can decrease by 36%than that without carbon price.(3)CCUS is one of important contributing factor to reduce CO2 emission in power sector.Generally speaking,the development of non-fossil fuels and energy efficiency improvement are two main drivers for carbon mitigation,but once the carbon price reaches up to CN￥106 t
1CO2,the CCUS will be required to equip with thermal power units and its contribution on carbon emission reduction will remarkably increase.When carbon price increases to CN￥150 t
1CO2 in 2050,the application of CCUS will account for 44%of total emission reduction.(4)In the scenario with carbon price of CN￥150 t
1CO2,power sector would be decarbonized significantly,and the CO2 intensity will be 0.22 kgCO2(kW h)
1,but power sector is far from the goal that achieving net zero emission.In order to realize the long-term low greenhouse gas emission development goal that proposed by the Paris Agreement,more efforts are needed to be put to further reduce the carbon emission reduction of power sector.Based on the above scenario analysis,the study proposes four recommendations on the low-carbon development of China's power sector:(1)improve the energy efficiency proactively and optimize the energy structure of power sector gradually;(2)promote the low-carbon transition of power sector by using market-based mechanism like carbon emission trading scheme to internalize the external cost of carbon emission;(3)give more emphasis on and support to the CCUS application in power sector.

Analysis on the influence factors of Bitcoin’s price based on VEC model

Background:Bitcoin,the most innovate digital currency as of now,created since 2008,even through experienced its ups and downs,still keeps drawing attentions to all parts of society.It relies on peer-to-peer network,achieved decentralization,anonymous and transparent.As the most representative digital currency,people curious to study how Bitcoin’price changes in the past.Methods:In this paper,we use monthly data from 2011 to 2016 to build a VEC model to exam how economic factors such as Custom price index,US dollar index,Dow jones industry average,Federal Funds Rate and gold price influence Bitcoin price.Result:From empirical analysis we find that all these variables do have a long-term influence.US dollar index is the biggest influence on Bitcoin price while gold price influence the least.Conclusion:From our result,we conclude that for now Bitcoin can be treated as a speculative asset,however,it is far from being a proper credit currency.

Research on Hybrid Model of Garlic Short-term Price Forecasting based on Big Data

Garlic prices fluctuate dramatically in recent years and it is very difficult to predict garlic prices.The autoregressive integrated moving average(ARIMA)model is currently the most important method for predicting garlic prices.However,the ARIMA model can only predict the linear part of the garlic prices,and cannot predict its nonlinear part.Therefore,it is urgent to adopt a method to analyze the nonlinear characteristics of garlic prices.After comparing the advantages and disadvantages of several major prediction models which used to forecast nonlinear time series,using support vector machine(SVM)model to predict the nonlinear part of garlic prices and establish ARIMA-SVM hybrid forecast model to predict garlic prices.The monthly average price data of garlic in 2010-2017 was used to test the effect of ARIMA model,SVM model and ARIMA-SVM model.The experimental results show that:(1)Garlic price is affected by many factors but the most is the supply and demand relationship;(2)The SVM model has a good effect in dealing with the nonlinear relationship of garlic prices;(3)The ARIMA-SVM hybrid model is better than the single ARIMA model and SVM model on the accuracy of garlic price prediction,it can be used as an effective method to predict the short-term price of garlic.

Fractional Birkhoffian Dynamics Based on Quasi-fractional Dynamics Models and Its Lie Symmetry

In order to investigate the dynamic behavior of non-conservative systems,the Lie symmetries and conserved quantities of fractional Birkhoffian dynamics based on quasi-fractional dynamics model are proposed and studied.The quasi-fractional dynamics model here refers to the variational problem based on the definition of RiemannLiouville fractional integral(RLFI),the variational problem based on the definition of extended exponentially fractional integral(EEFI),and the variational problem based on the definition of fractional integral extended by periodic laws(FIEPL).First,the fractional Pfaff-Birkhoff principles based on quasi-fractional dynamics models are established,and the corresponding Birkhoff’s equations and the determining equations of Lie symmetry are obtained.Second,for fractional Birkhoffian systems based on quasi-fractional models,the conditions and forms of conserved quantities are given,and Lie symmetry theorems are proved.The Pfaff-Birkhoff principles,Birkhoff’s equations and Lie symmetry theorems of quasi-fractional Birkhoffian systems and classical Birkhoffian systems are special cases of this article.Finally,some examples are given.

Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model

This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows: first, the average house price is 12 436 yuan(RMB)/m^2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.

Empirical Study on the Impact of Rural Labor Force Flow on the Price of Agricultural Products——A Method Based on VEC Model

Based on the research introduction of domestic and foreign scholars,dynamic equilibrium between the rural labor force flow and the price of agricultural product is analyzed by VEC model,according to the data of the rural labor force flow and the price of agricultural products in the years 1990-2007.Chows breakpoint test is used to measure the stage characteristics of the impact of rural labor force flow on the price of agricultural product.Result shows that there is a long-term and stationary relationship between the flow quantity of rural labor force and the price of agricultural product.Rural labor force flow,as an exogenous force,affects the agricultural production,and further influences the price fluctuation of agricultural products.Impact of rural labor force flow on the price of agricultural product is from weak to strong,then grows gradually weaker,and reaches its peak value at the year 1998.With the development of rural society and economy and the market process,rural labor force flow endogenously affects the price of agricultural product,which has periodic characteristics.In order to achieve a dual stabilization of the rural labor force flow and the price of agricultural products,the following countermeasures are put forward:vigorously developing vocational education,increasing the support for agricultural production,and making active employment measures.

Technological anxiety:Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood.Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an“icing on the cake”or“adding fuel to the fire”needs further study.This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy.First,from the theoretical logic and the economic development law,this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs.Then,based on the panel data of 269 cities in China from 2006 to 2021,we use the two-way fixed effect model,dynamic threshold model,and two-stage intermediary effect model.The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism.Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the“creation effect”.In other words,advanced digital technology has created additional jobs,and the overall supply of employment in the labor market has increased.The conclusion is still valid after the endogeneity identification and robustness test.In addition,the positive effect has a nonlinear effect on the network scale.When the installation density of industrial robots exceeds a particular threshold value,the division of labor continues to deepen under the combined action of the production efficiency and compensation effects,which will cause enterprises to increase labor demand further.Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions.This study concludes that in the digital China era,the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market.This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

Including predator presence in a refined model for assessing resistance of alfalfa cultivar to aphids

The aphid quantity ratio（AQR） is defined as the number of aphids on each cultivar divided by the number of aphids on all cultivars. AQR is based on the correlation between aphid populations and their host plants and is an important tool that has been utilized in evaluating Medicago sativa（alfalfa） cultivar resistance to aphids. However, assessment of alfalfa resistance to aphids can be confused by the presence of aphid predators, causing the assessment of plant resistance to aphids to be based on incorrect aphid population data. To refine the AQR and account for the effect of predators on aphid population assessments, we introduced a parameter ‘α＇, corresponding to the predator quantity ratio, and used αAQR as the ratio to quantify aphid populations. Populations of both aphids（4 species） and their predators（12 species） occurring in 28 M. sativa cultivars were sampled over two years at a research station near Cangzhou, Hebei Province, China. Results showed that the most suitable evaluation period was from May to June, as the aphid population was stable during this period. Compared with the AQR method, the predator population numbers based on the αAQR had a significant inverse relationship with aphid population numbers and the 28 cultivars were clustered into three classes： the resistant class, tolerant class, and susceptible class. In addition, 17 cultivars were reassigned when evaluated using αAQR. All numerical values calculated by αAQR were displayed as a Gaussian distribution, which showed that the 28 cultivars could be clustered into nine groups using a median value（±SE） of 1±0.1. Hence, ongoing alfalfa breeding trials will be assessed using the αAQR to establish a robust system that includes agronomic performance parameters in order to generalize the new method for further studies.

Balance of Datum Land Prices Among Cities Based on the City Gravitation Model and Stochastic Diffusion Equation

A balance of urban datum land prices is achieved to harmonize regional land prices and make the prices truly reflect different economic development levels and land prices among cities. The current piecewise linear interpolation balance method widely used has two drawbacks that always lead to an unsatisfactory balance among some cities. When the excess of land price in the central city to the surrounding zone reaches a certain degree, land price in the circumjacent city is not only consistent with the local land grade and land use level, but also influenced by the diffusion of land price in the central city. Thus, a new balanced scheme of datum land prices based on the city gravitation model and stochastic diffusion equation is brought forward. Finally, the new method is examined in the practice of datum land price balance in Hubei Province, China.