Available water for human needs and agriculture is a growing global concern. Agriculture uses approximately 70% of global freshwater, mainly for irrigation. The Lower Fraser Valley (LFV), British Columbia, is one of t...Available water for human needs and agriculture is a growing global concern. Agriculture uses approximately 70% of global freshwater, mainly for irrigation. The Lower Fraser Valley (LFV), British Columbia, is one of the most productive agricultural regions in Canada, supporting livestock production and a wide variety of crops. Water scarcity is a growing concern that threatens the long-term productivity, sustainability, and economic viability of the LFV’s agriculture. We used the BC Agriculture Water Demand Model as a tool to determine how crop choice, irrigation system, and land-use changes can affect predicted water requirements under these different conditions, which can aid stakeholders to formulate better management decisions. We conducted a comparative assessment of the irrigation water demand of seven major commercial crops, by distinct soil management groups, at nineteen representative sites, that use both sprinkler vs drip irrigation. Drip irrigation was consistently more water-efficient than sprinkler irrigation for all crops. Of the major commercial crops assessed, raspberries were the most efficient in irrigation water demand, while forage and pasture had the highest calculated irrigation water demand. Significant reductions in total irrigation water demand (up to 57%) can be made by switching irrigation systems and/or crops. This assessment can aid LFV growers in their land-use choices and could contribute to the selection of water management decisions and agricultural policies.展开更多
Induced travel is an important component of travel demand and increasing attention has been paid to building analytical model to get more precise travel demand forecasting. In general, induced demand can be defined in...Induced travel is an important component of travel demand and increasing attention has been paid to building analytical model to get more precise travel demand forecasting. In general, induced demand can be defined in terms of additional trips that would be made if travel conditions improved (less congested, lower vehicle costs or tolls). In this paper the induced demand resulting from higher design speeds and, therefore by less travel time, for the High Speed 1 in UK will be modelled on the basis of the relationship between existing High Speed Rail demand (dependent variable) to existing High Speed Rail travel times and costs. The covariates include socioeconomic variables related to population and employment in the zones connected by the High Speed Rail services. This model has been calibrated by mean of a before and after study carried on the corridor, when the new High Speed Rail services was introduced. Elasticities of induced travel (trips and VMT) have been computed with respect to fares, travel time and service frequency.展开更多
A relevance vector machine(RVM)based demand prediction model is explored for efficient seismic fragility analysis(SFA)of a bridge structure.The proposed RVM model integrates both record-to-record variations of ground ...A relevance vector machine(RVM)based demand prediction model is explored for efficient seismic fragility analysis(SFA)of a bridge structure.The proposed RVM model integrates both record-to-record variations of ground motions and uncertainties of parameters characterizing the bridge model.For efficient fragility computation,ground motion intensity is included as an added dimension to the demand prediction model.To incorporate different sources of uncertainty,random realizations of different structural parameters are generated using Latin hypercube sampling technique.Mean fragility,along with its dispersions,is estimated based on the log-normal fragility model for different critical components of a bridge.The effectiveness of the proposed RVM model-based SFA of a bridge structure is elucidated numerically by comparing it with fragility results obtained by the commonly used SFA approaches,while considering the most accurate direct Monte Carlo simulation-based fragility estimates as the benchmark.The proposed RVM model provides a more accurate estimate of fragility than conventional approaches,with significantly less computational effort.In addition,the proposed model provides a measure of uncertainty in fragility estimates by constructing confidence intervals for the fragility curves.展开更多
In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the mod...In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).展开更多
Recent seismic events have raised concerns over the safety and vulnerability of reinforced concrete moment resisting frame ＂RC-MRF＂ buildings. The seismic response of such buildings is greatly dependent on the compu...Recent seismic events have raised concerns over the safety and vulnerability of reinforced concrete moment resisting frame ＂RC-MRF＂ buildings. The seismic response of such buildings is greatly dependent on the computational tools used and the inherent assumptions in the modelling process. Thus, it is essential to investigate the sensitivity of the response demands to the corresponding modelling assumption. Many parameters and assumptions are justified to generate effective structural finite element（FE） models of buildings to simulate lateral behaviour and evaluate seismic design demands. As such, the present study focuses on the development of reliable FE models with various levels of refinement. The effects of the FE modelling assumptions on the seismic response demands on the design of buildings are investigated. the predictive ability of a FE model is tied to the accuracy of numerical analysis; a numerical analysis is performed for a series of symmetric buildings in active seismic zones. The results of the seismic response demands are presented in a comparative format to confirm drift and strength limits requirements. A proposed model is formulated based on a simplified modeling approach, where the most refined model is used to calibrate the simplified model.展开更多
The electricity needs of populations in Cameroon are increasing and are still very inadequate. Companies, public buildings and households are facing frequent blackout which constrain development and social well-being....The electricity needs of populations in Cameroon are increasing and are still very inadequate. Companies, public buildings and households are facing frequent blackout which constrain development and social well-being. Therefore, the present work tried to forecast the electricity demand in the residential sector in Cameroon, in order to contribute significantly to the mastery of electricity consumption and highlight decision-makers in this sector. Six macroeconomics parameters covering the period 1994-2014 are used for these issues. Stationarity tests within gross domestic product, gross domestic product per capita, electricity consumption, population and numbers of subscribers and households respectively;reveal that all the series are I(1). Thus, the VAR (Vector Autoregressive) model has been retained to forecast the electricity demand until 2020. The cusum test and the cusum of squared test attest the stability of that model with a margin of error of 0.02%. Previsions are then more reliable and show that the electric request will skip from 1721 GWh in 2014 to more than 2481 GWh in 2020 approximatively, following a growing yearly rate of 5.36%. In order to reach its emergence, Cameroon ought to speed up its production in the domain of hydroelectric and thermal grid in order to meet the requirements in electric power in short and long term.展开更多
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 beh...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.展开更多
By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal de...By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal demand system( RSDAIDS) is used to estimate the income and price elasticity of major imported agriculture textile material from the major sources based on the data from 1992 to 2015. The results are shown as follows.( 1) Although the dependency on imported cotton is lower than wool, the fluctuation of cotton import is much more drastic; China's demand for cotton is relatively price elastic with higher expenditure elasticity compared with wool; besides,the existence of complementarity is proved between imported cotton and wool.( 2) According to the import elasticity of cotton,demand for cotton imported from India shows priority over cotton from other sources; demand for cotton imported from America is the most price-sensitive one; substitution among cotton from different sources is weak.( 3) According to the import elasticity of wool,wool imported from Uruguay has bright market prospects. In addition,wool imported from Australia has irreplaceable advantage than that from New Zealand.展开更多
This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport...This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.展开更多
Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item ...Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item and unification of groundwater抯 economic, environmental and ecological functions were taken into account. Based on eco-environmental water demand at Da抋n in Jilin province, a three-dimensional simulation and optimized management model of groundwater systems was established. All water balance components of groundwater systems in 1998 and 1999 were simulated with this model and the best optimal exploitation scheme of groundwater systems in 2000 was determined, so that groundwater resource was efficiently utilized and good economic, ecologic and social benefits were obtained.展开更多
Lacuna and Universal Model provides a new terminology and classification for the factors behind the success and failure of cross-cultural media content,and thus forms an analysis framework for the study of the cross-c...Lacuna and Universal Model provides a new terminology and classification for the factors behind the success and failure of cross-cultural media content,and thus forms an analysis framework for the study of the cross-cultural audiences'need.According to this model,the audience will dislike or not select foreign media content under these circumstances:(1)audiences find that the content is irrelevant or unsuitable;(2)audiences cannot comprehend the content;3)they do not like the style of such content.This model also argues that cross-cultural media content is successfully spread under these circumstances:(1)the media content shows attractive attribute to cross-cultural audience;(2)the media content is open to alternative readings.展开更多
This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand...This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.展开更多
This paper takes the total yield of products that need refrigerated transport as the impact factors of transport aggregate of cold chain logistics,such as meat,aquatic products,quick-frozen noodle,fruits,vegetables,da...This paper takes the total yield of products that need refrigerated transport as the impact factors of transport aggregate of cold chain logistics,such as meat,aquatic products,quick-frozen noodle,fruits,vegetables,dairy,and medicine.Through selecting the consumption data of urban residents on transported products via cold chain in Jiangsu Province from 2005 to 2000 as sample,this paper establishes grey prediction model GM(1,1) of cold chain logistics demand and uses DPS7.05 software for test,to predict the cold chain logistics demand of urban residents in Jiangsu Province during the Twelfth Five-Year Plan period.The results show that in the period 2010-2015,the cold chain logistics demand of urban residents in Jiangsu Province is 1 151.589 1,1 185.136 6,1 219.661 3,1 255.191 8,1 291.757 3,1 329.388 1 t respectively;in the period 2005-2010,the cold chain logistics demand of urban residents in Jiangsu Province increases at annual growth rate of 3.9%;in the period 2011-2015,the growth rate declines to some extent,increasing slowly at rate of 2.9%.展开更多
This paper proposes a modeling system developed in order to analyze the urban freight transport and logistics within urban and metropolitan areas. A review of models developed to simulate this segment of mobility is a...This paper proposes a modeling system developed in order to analyze the urban freight transport and logistics within urban and metropolitan areas. A review of models developed to simulate this segment of mobility is also reported. The review analysis highlights the limits of models for the ex-ante assessment of city logistics measures. For this reason this paper proposes a new modeling system approach for the assessment of city logistics measures. It is made of different steps approaching problems related to quantity OD （Origin-Destination） flows, restocking type OD flows, delivery OD flows, delivery OD flows for time slice and vehicle type, and vehicle OD flows. This modeling system has been specified and calibrated using some surveys carried out in the inner area of Rome where more than 500 truck drivers and more than 600 retailers have been interviewed.展开更多
Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system(GPS) data to delineate the ...Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system(GPS) data to delineate the life circles. This method, however, is constrained by GPS data, and it can only be applied in the GPS surveyed communities. To address this limitation, this study developed a generalizable delineation method without the constraint of behavioral data. According to previous research, the community life circle consists of the walking-accessible range and internal structure. The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle, as the range can be delineated primarily based on environmental data. Therefore, behavioral demand estimation models were established through logistic regression and machine learning techniques, including decision trees and ensemble learning. The model with the lowest error rate was chosen as the final estimation model for each type of land. Finally, we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method. This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models, which learn the relationships between environmental contexts, population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data. Furthermore, the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning, and activity space estimation of the population in evaluating and improving the urban policies.展开更多
Urban land intensive use is an important indicator in harmonizing the relationship between land supply and demand. The system dynamics(SD) can be used to construct the feedback loop between urban construction land sup...Urban land intensive use is an important indicator in harmonizing the relationship between land supply and demand. The system dynamics(SD) can be used to construct the feedback loop between urban construction land supply and demand and index variable function. Based on this, this study built a supply and demand system dynamic model of urban construction land for Chang-Zhu-Tan urban agglomeration. This model can simulate the change trends of supply and demand of construction land, industrial land, and residential land in 2016–2030 by three scenarios of low, medium, and high intensity modes. The results showed that the scale of construction land of urban agglomeration is expanding, with a rapid increase rate for the urban construction land. The scale and speed of land use based on the three intensity modes existed differences. The large scale and supply of construction land in the low intensity mode caused easily the waste of land resources. In high intensity mode, the scale and supply of construction land were reduced against the healthy development of new-type urbanization. In the medium intensity mode, the scale and supply of land use adapted to the socio-economic development and at the same time reflected the concept of modern urban development. In addition, the results of this study found that the proportion of industrial land in construction land ranged from 15% to 21%, which increased year by year in the low intensity mode, and decreased slowly and stabilized in medium and high intensity modes. The proportion of residential land in construction land ranged from 27% to 35%, which decreased in the low and the medium intensity modes, and maintained a high level in the higher intensity mode. This study contributes to provide scientific reference for decision-making optimization of land supply and demand, urban planning, and land supply-side reform.展开更多
Within the healthcare context is very important to foster the dynamics leading to positive experiences at work, in order to promote work motivation and well-being. This study investigated the influence of some persona...Within the healthcare context is very important to foster the dynamics leading to positive experiences at work, in order to promote work motivation and well-being. This study investigated the influence of some personal and job resources and of some job demands on the three dimensions (absorption, work enjoyment, intrinsic work motivation) of flow at work, on the basis of Job Demands-Resources Model. Flow at work is an inner experience arising during an activity in which people are immersed, feel motivated and enjoy it. Studies suggest that resources are the main antecedents of the flow experience. Respondents to the questionnaire were 197 nurses. Multiple regressions were performed to detect the resources and the demands that influence the three dimensions of flow at work. As expected, resources positively influenced the dimensions of flow at work, particularly work enjoyment. Job demands positively influenced absorption and negatively influenced the other two dimensions of flow at work. Human resources managers should promote flow at work supporting the availability of resources and monitoring the job demands.展开更多
The traditional newsvendor model assumes that a decision-maker is risk-neutral. However, in actuality, a decisionmaker's order behavior is often influenced by waste-averse preference and stockout-averse preference...The traditional newsvendor model assumes that a decision-maker is risk-neutral. However, in actuality, a decisionmaker's order behavior is often influenced by waste-averse preference and stockout-averse preference. We extend the newsvendor model with consideration of averse preferences to investigate how the decision results of the previous period impact the order behavior of the current period, and design an inventory decision-making behavior experiment. Results from the study demonstrate that the order behavior of both a group and an individual exhibits a demand chasing phenomenon, and the former is more significant. Through the interval estimation of the decision maker's order quantity, by the maximum likelihood method we find that the stockout-averse preference has an effect on the decision-making when the prior period is insufficient, causing the current period order quantity larger than the expected profit-maximizing order quantity. In a similar way, waste-averse preference has an effect on decision-making when the prior period is surplus, resulting in the current period order quantity smaller than the expected profit-maximizing order quantity. Finally, we investigate the formation mechanism of demand chasing phenomenon from the perspective of the averse preferences, and propose that this phenomenon is a decision maker's cognitive reaction to stochastic demand environment.展开更多
In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individua...In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.展开更多
This paper analyzes the relationship between the stock of infrastructure and income increases using data from 15 typical countries,including China,and measures the gap between China and npper-middlle-income countries ...This paper analyzes the relationship between the stock of infrastructure and income increases using data from 15 typical countries,including China,and measures the gap between China and npper-middlle-income countries using the Euclidean distance.By constructing a domestic infrastructure investment demand model,this paper provides the basis for determining the growth rates for infrastructure investment demand under the given economic development goals and assessing the rationality of such growth rates.The paper finds that,as the per-capita income level increases, the total infrastructure demand rises but different types of infrastructure stock grow at different paces.Using the 2004 domestic infrastructure level as the benchmark for international comparison,we find it imperative for China to further boost resource infrastructure construction in the future and keep resource infrastructure investment growing at an average annual rate of 15%-24%.The infrastructure investment growth rate should be kept above the nominal GDP growth rate.展开更多
文摘Available water for human needs and agriculture is a growing global concern. Agriculture uses approximately 70% of global freshwater, mainly for irrigation. The Lower Fraser Valley (LFV), British Columbia, is one of the most productive agricultural regions in Canada, supporting livestock production and a wide variety of crops. Water scarcity is a growing concern that threatens the long-term productivity, sustainability, and economic viability of the LFV’s agriculture. We used the BC Agriculture Water Demand Model as a tool to determine how crop choice, irrigation system, and land-use changes can affect predicted water requirements under these different conditions, which can aid stakeholders to formulate better management decisions. We conducted a comparative assessment of the irrigation water demand of seven major commercial crops, by distinct soil management groups, at nineteen representative sites, that use both sprinkler vs drip irrigation. Drip irrigation was consistently more water-efficient than sprinkler irrigation for all crops. Of the major commercial crops assessed, raspberries were the most efficient in irrigation water demand, while forage and pasture had the highest calculated irrigation water demand. Significant reductions in total irrigation water demand (up to 57%) can be made by switching irrigation systems and/or crops. This assessment can aid LFV growers in their land-use choices and could contribute to the selection of water management decisions and agricultural policies.
文摘Induced travel is an important component of travel demand and increasing attention has been paid to building analytical model to get more precise travel demand forecasting. In general, induced demand can be defined in terms of additional trips that would be made if travel conditions improved (less congested, lower vehicle costs or tolls). In this paper the induced demand resulting from higher design speeds and, therefore by less travel time, for the High Speed 1 in UK will be modelled on the basis of the relationship between existing High Speed Rail demand (dependent variable) to existing High Speed Rail travel times and costs. The covariates include socioeconomic variables related to population and employment in the zones connected by the High Speed Rail services. This model has been calibrated by mean of a before and after study carried on the corridor, when the new High Speed Rail services was introduced. Elasticities of induced travel (trips and VMT) have been computed with respect to fares, travel time and service frequency.
文摘A relevance vector machine(RVM)based demand prediction model is explored for efficient seismic fragility analysis(SFA)of a bridge structure.The proposed RVM model integrates both record-to-record variations of ground motions and uncertainties of parameters characterizing the bridge model.For efficient fragility computation,ground motion intensity is included as an added dimension to the demand prediction model.To incorporate different sources of uncertainty,random realizations of different structural parameters are generated using Latin hypercube sampling technique.Mean fragility,along with its dispersions,is estimated based on the log-normal fragility model for different critical components of a bridge.The effectiveness of the proposed RVM model-based SFA of a bridge structure is elucidated numerically by comparing it with fragility results obtained by the commonly used SFA approaches,while considering the most accurate direct Monte Carlo simulation-based fragility estimates as the benchmark.The proposed RVM model provides a more accurate estimate of fragility than conventional approaches,with significantly less computational effort.In addition,the proposed model provides a measure of uncertainty in fragility estimates by constructing confidence intervals for the fragility curves.
基金supported by the Fundamental Research Funds for the Central Universities[Grant No.JBK1507159]
文摘In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).
基金Scientific Research Deanship,Taibah University Grant No.6363/436
文摘Recent seismic events have raised concerns over the safety and vulnerability of reinforced concrete moment resisting frame ＂RC-MRF＂ buildings. The seismic response of such buildings is greatly dependent on the computational tools used and the inherent assumptions in the modelling process. Thus, it is essential to investigate the sensitivity of the response demands to the corresponding modelling assumption. Many parameters and assumptions are justified to generate effective structural finite element（FE） models of buildings to simulate lateral behaviour and evaluate seismic design demands. As such, the present study focuses on the development of reliable FE models with various levels of refinement. The effects of the FE modelling assumptions on the seismic response demands on the design of buildings are investigated. the predictive ability of a FE model is tied to the accuracy of numerical analysis; a numerical analysis is performed for a series of symmetric buildings in active seismic zones. The results of the seismic response demands are presented in a comparative format to confirm drift and strength limits requirements. A proposed model is formulated based on a simplified modeling approach, where the most refined model is used to calibrate the simplified model.
文摘The electricity needs of populations in Cameroon are increasing and are still very inadequate. Companies, public buildings and households are facing frequent blackout which constrain development and social well-being. Therefore, the present work tried to forecast the electricity demand in the residential sector in Cameroon, in order to contribute significantly to the mastery of electricity consumption and highlight decision-makers in this sector. Six macroeconomics parameters covering the period 1994-2014 are used for these issues. Stationarity tests within gross domestic product, gross domestic product per capita, electricity consumption, population and numbers of subscribers and households respectively;reveal that all the series are I(1). Thus, the VAR (Vector Autoregressive) model has been retained to forecast the electricity demand until 2020. The cusum test and the cusum of squared test attest the stability of that model with a margin of error of 0.02%. Previsions are then more reliable and show that the electric request will skip from 1721 GWh in 2014 to more than 2481 GWh in 2020 approximatively, following a growing yearly rate of 5.36%. In order to reach its emergence, Cameroon ought to speed up its production in the domain of hydroelectric and thermal grid in order to meet the requirements in electric power in short and long term.
文摘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.
基金Industrial Research of National Wool and Csahmere Industry Technology System,China(No.CARS-40-20)
文摘By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal demand system( RSDAIDS) is used to estimate the income and price elasticity of major imported agriculture textile material from the major sources based on the data from 1992 to 2015. The results are shown as follows.( 1) Although the dependency on imported cotton is lower than wool, the fluctuation of cotton import is much more drastic; China's demand for cotton is relatively price elastic with higher expenditure elasticity compared with wool; besides,the existence of complementarity is proved between imported cotton and wool.( 2) According to the import elasticity of cotton,demand for cotton imported from India shows priority over cotton from other sources; demand for cotton imported from America is the most price-sensitive one; substitution among cotton from different sources is weak.( 3) According to the import elasticity of wool,wool imported from Uruguay has bright market prospects. In addition,wool imported from Australia has irreplaceable advantage than that from New Zealand.
文摘This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.
基金The Key Project of the National Ninth-Five-Year Plan No. 96-004-02-09The 48Project of Ministry of Water Resources No. 985106The Project of Chinese Academy of Sciences
文摘Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item and unification of groundwater抯 economic, environmental and ecological functions were taken into account. Based on eco-environmental water demand at Da抋n in Jilin province, a three-dimensional simulation and optimized management model of groundwater systems was established. All water balance components of groundwater systems in 1998 and 1999 were simulated with this model and the best optimal exploitation scheme of groundwater systems in 2000 was determined, so that groundwater resource was efficiently utilized and good economic, ecologic and social benefits were obtained.
文摘Lacuna and Universal Model provides a new terminology and classification for the factors behind the success and failure of cross-cultural media content,and thus forms an analysis framework for the study of the cross-cultural audiences'need.According to this model,the audience will dislike or not select foreign media content under these circumstances:(1)audiences find that the content is irrelevant or unsuitable;(2)audiences cannot comprehend the content;3)they do not like the style of such content.This model also argues that cross-cultural media content is successfully spread under these circumstances:(1)the media content shows attractive attribute to cross-cultural audience;(2)the media content is open to alternative readings.
文摘This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.
基金Supporte by College Philosophical Social Science Foundation of Jiangsu Provincial Department of Education in 2009 (09SJB790008)Science and Technology Support Project of Huaian City in 2009(HAS2009045-1)Funds from Huaian Municipal Bureau of Communications
文摘This paper takes the total yield of products that need refrigerated transport as the impact factors of transport aggregate of cold chain logistics,such as meat,aquatic products,quick-frozen noodle,fruits,vegetables,dairy,and medicine.Through selecting the consumption data of urban residents on transported products via cold chain in Jiangsu Province from 2005 to 2000 as sample,this paper establishes grey prediction model GM(1,1) of cold chain logistics demand and uses DPS7.05 software for test,to predict the cold chain logistics demand of urban residents in Jiangsu Province during the Twelfth Five-Year Plan period.The results show that in the period 2010-2015,the cold chain logistics demand of urban residents in Jiangsu Province is 1 151.589 1,1 185.136 6,1 219.661 3,1 255.191 8,1 291.757 3,1 329.388 1 t respectively;in the period 2005-2010,the cold chain logistics demand of urban residents in Jiangsu Province increases at annual growth rate of 3.9%;in the period 2011-2015,the growth rate declines to some extent,increasing slowly at rate of 2.9%.
文摘This paper proposes a modeling system developed in order to analyze the urban freight transport and logistics within urban and metropolitan areas. A review of models developed to simulate this segment of mobility is also reported. The review analysis highlights the limits of models for the ex-ante assessment of city logistics measures. For this reason this paper proposes a new modeling system approach for the assessment of city logistics measures. It is made of different steps approaching problems related to quantity OD （Origin-Destination） flows, restocking type OD flows, delivery OD flows, delivery OD flows for time slice and vehicle type, and vehicle OD flows. This modeling system has been specified and calibrated using some surveys carried out in the inner area of Rome where more than 500 truck drivers and more than 600 retailers have been interviewed.
基金Under the auspices of the National Natural Science Foundation of China(No.41571144)。
文摘Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system(GPS) data to delineate the life circles. This method, however, is constrained by GPS data, and it can only be applied in the GPS surveyed communities. To address this limitation, this study developed a generalizable delineation method without the constraint of behavioral data. According to previous research, the community life circle consists of the walking-accessible range and internal structure. The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle, as the range can be delineated primarily based on environmental data. Therefore, behavioral demand estimation models were established through logistic regression and machine learning techniques, including decision trees and ensemble learning. The model with the lowest error rate was chosen as the final estimation model for each type of land. Finally, we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method. This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models, which learn the relationships between environmental contexts, population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data. Furthermore, the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning, and activity space estimation of the population in evaluating and improving the urban policies.
基金National Social Science Foundation of China,No.15BJY051Social Science Foundation of Hunan Province,No.16ZDB04,No.13YBA016+2 种基金Research Project of Appraisement Committee of Social Sciences Research Achievements of Hunan Province,No.XSP18ZDI031Natural Science Foundation of Hunan Province,No.2017JJ2264Science&Technology Research Project of the Department of Land and Resource of Hunan Province,No.2014-13
文摘Urban land intensive use is an important indicator in harmonizing the relationship between land supply and demand. The system dynamics(SD) can be used to construct the feedback loop between urban construction land supply and demand and index variable function. Based on this, this study built a supply and demand system dynamic model of urban construction land for Chang-Zhu-Tan urban agglomeration. This model can simulate the change trends of supply and demand of construction land, industrial land, and residential land in 2016–2030 by three scenarios of low, medium, and high intensity modes. The results showed that the scale of construction land of urban agglomeration is expanding, with a rapid increase rate for the urban construction land. The scale and speed of land use based on the three intensity modes existed differences. The large scale and supply of construction land in the low intensity mode caused easily the waste of land resources. In high intensity mode, the scale and supply of construction land were reduced against the healthy development of new-type urbanization. In the medium intensity mode, the scale and supply of land use adapted to the socio-economic development and at the same time reflected the concept of modern urban development. In addition, the results of this study found that the proportion of industrial land in construction land ranged from 15% to 21%, which increased year by year in the low intensity mode, and decreased slowly and stabilized in medium and high intensity modes. The proportion of residential land in construction land ranged from 27% to 35%, which decreased in the low and the medium intensity modes, and maintained a high level in the higher intensity mode. This study contributes to provide scientific reference for decision-making optimization of land supply and demand, urban planning, and land supply-side reform.
文摘Within the healthcare context is very important to foster the dynamics leading to positive experiences at work, in order to promote work motivation and well-being. This study investigated the influence of some personal and job resources and of some job demands on the three dimensions (absorption, work enjoyment, intrinsic work motivation) of flow at work, on the basis of Job Demands-Resources Model. Flow at work is an inner experience arising during an activity in which people are immersed, feel motivated and enjoy it. Studies suggest that resources are the main antecedents of the flow experience. Respondents to the questionnaire were 197 nurses. Multiple regressions were performed to detect the resources and the demands that influence the three dimensions of flow at work. As expected, resources positively influenced the dimensions of flow at work, particularly work enjoyment. Job demands positively influenced absorption and negatively influenced the other two dimensions of flow at work. Human resources managers should promote flow at work supporting the availability of resources and monitoring the job demands.
基金Funded by the Fundamental Research Funds for the Central Universities of China(No.26816WTD23)Key Projects of Scientific Research and Development Plan,Chengdu Railway Bureau,China(No.CX1716)Sichuan Science and Technology Project,China(Title:Safety operation behavior mechanism of rail transit dispatcher taking the Chengdu metro as an example)
文摘The traditional newsvendor model assumes that a decision-maker is risk-neutral. However, in actuality, a decisionmaker's order behavior is often influenced by waste-averse preference and stockout-averse preference. We extend the newsvendor model with consideration of averse preferences to investigate how the decision results of the previous period impact the order behavior of the current period, and design an inventory decision-making behavior experiment. Results from the study demonstrate that the order behavior of both a group and an individual exhibits a demand chasing phenomenon, and the former is more significant. Through the interval estimation of the decision maker's order quantity, by the maximum likelihood method we find that the stockout-averse preference has an effect on the decision-making when the prior period is insufficient, causing the current period order quantity larger than the expected profit-maximizing order quantity. In a similar way, waste-averse preference has an effect on decision-making when the prior period is surplus, resulting in the current period order quantity smaller than the expected profit-maximizing order quantity. Finally, we investigate the formation mechanism of demand chasing phenomenon from the perspective of the averse preferences, and propose that this phenomenon is a decision maker's cognitive reaction to stochastic demand environment.
文摘In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.
文摘This paper analyzes the relationship between the stock of infrastructure and income increases using data from 15 typical countries,including China,and measures the gap between China and npper-middlle-income countries using the Euclidean distance.By constructing a domestic infrastructure investment demand model,this paper provides the basis for determining the growth rates for infrastructure investment demand under the given economic development goals and assessing the rationality of such growth rates.The paper finds that,as the per-capita income level increases, the total infrastructure demand rises but different types of infrastructure stock grow at different paces.Using the 2004 domestic infrastructure level as the benchmark for international comparison,we find it imperative for China to further boost resource infrastructure construction in the future and keep resource infrastructure investment growing at an average annual rate of 15%-24%.The infrastructure investment growth rate should be kept above the nominal GDP growth rate.
