Delineation of an Urban Community Life Circle Based on a Machine-Learning Estimation of Spatiotemporal Behavioral Demand

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.

Irrigation Water Demand Model as a Comparative Tool for Assessing Effects of Land Use Changes for Agricultural Crops in Fraser Valley, Canada

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.

Seismic fragility analysis of bridges by relevance vector machine based demand prediction model

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.

Impact of Electric Vehicles on Travel and Electricity Demand in Metropolitan Area： A Case Study in Nagoya

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.

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

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

Using structured systems analysis to design an integrated system for transport planning and environmental analysis

This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate processes or 'systems'. Six serious shortcomings are identified in prevailing approaches to accounting for the environmental impacts of transport plans. The application of systems analysis has elucidated opportunities for overcoming these problems by integrating the two processes. The paper highlights the benefits of using these methods to direct research into, and development of, an integrated transport planning- environmental analysis system. Techniques applied are data flow diagrams, a Venn diagram and an entity-relationship diagram. Significant potential exists for integration within a geographic information system(GIS), although adoption of integrated methods by transport planners is likely to be incremental. Research confirms the usefulness of systems analysis in guiding the development of a GIS application to accommodate integrated transport planning and environmental analysis. Systems analysis also facilitates more careful and effective design of the databases underlying GIS analysis.

Seismic fragility assessment of RC frame structure designed according to modern Chinese code for seismic design of buildings

Following several damaging earthquakes in China, research has been devoted to find the causes of the collapse of reinforced concrete （RC） building sand studying the vulnerability of existing buildings. The Chinese Code for Seismic Design of Buildings （CCSDB） has evolved over time, however, there is still reported earthquake induced damage of newly designed RC buildings. Thus, to investigate modern Chinese seismic design code, three low-, mid- and high-rise RC frames were designed according to the 2010 CCSDB and the corresponding vulnerability curves were derived by computing a probabilistic seismic demand model （PSDM）.The PSDM was computed by carrying out nonlinear time history analysis using thirty ground motions obtained from the Pacific Earthquake Engineering Research Center. Finally, the PSDM was used to generate fragility curves for immediate occupancy, significant damage, and collapse prevention damage levels. Results of the vulnerability assessment indicate that the seismic demands on the three different frames designed according to the 2010 CCSDB meet the seismic requirements and are almost in the same safety level.

Performance-based seismic assessment of skewed bridges with and without considering soil-foundation interaction effects for various site classes

The seismic behavior of skewed bridges has not been well studied compared to straight bridges. Skewed bridges have shown extensive damage, especially due to deck rotation, shear keys failure, abutment unseating and column- bent drift. This research, therefore, aims to study the behavior of skewed and straight highway overpass bridges both with and without taking into account the effects of Soil-Structure Interaction （SSI） due to near-fault ground motions. Due to several sources of uncertainty associated with the ground motions, soil and structure, a probabilistic approach is needed. Thus, a probabilistic methodology similar to the one developed by the Pacific Earthquake Engineering Research Center （PEER） has been utilized to assess the probability of damage due to various levels of shaking using appropriate intensity measures with minimum dispersions. The probabilistic analyses were performed for various bridge configurations and site conditions, including sand ranging from loose to dense and clay ranging from soft to stiff, in order to evaluate the effects. The results proved a considerable susceptibility of skewed bridges to deck rotation and shear keys displacement. It was also found that SSI had a decreasing effect on the damage probability for various demands compared to the fixed-base model without including SSI. However, deck rotation for all types of the soil and also abutment unseating for very loose sand and soft clay showed an increase in damage probability compared to the fixed-base model. The damage probability for various demands has also been found to decrease with an increase of soil strength for both sandy and clayey sites. With respect to the variations in the skew angle, an increase in skew angle has had an increasing effect on the amplitude of the seismic response for various demands. Deck rotation has been very sensitive to the increase in the skew angle; therefore, as the skew angle increased, the deck rotation responded accordingly. Furthermore, abutment unseating showed an increasing trend due to an increase in skew angle for both fixed-base and SSI models.

Study on individualized information service for the reader in the library based on the network

With the massive increase of digital resource based on the network,it becomes very important that how to help readers acquire the information needed according to the individualized requirement and interest in an accurate,convenient and prompt method. Therefore,it is very urgent to investigate individualized information service of library. In this paper,based on the development of the individualized information service for the reader in the college library,the individualized information service is clarified by using three perspectives,including establishment of individualized information demand model,integration of internal and external resource and protection of the reader privacy. Finally,the corresponding strategy and related measure are presented.

A Delivery Approach Modeling for Urban Freight Restocking

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.

An iterative approach to an integrated land use and transportation planning tool for small urban areas

There has been increasing interests in developing land use models for small urban areas for various planning applications such as air quality conformity analysis. The output of a land use model can serve as a major input to a transportation model; conversely, transportation model output can provide a critical input to a land use model. The connection between the two models can be achieved by an accessibility measure. This paper presents an iterative approach to solving a regression-based land use model and a transportation model with combined trip distribution- assignment. A case study using data from a small urban area is presented to illustrate the application of the proposed modeling framework. Tests show that the procedures can converge, and the modeling framework can be a valuable tool for planners and decision-makers in evaluating land use policies and transportation investment strategies.

Pricing Power of China's Cocoon and Silk Products in International Market:An Empirical Analysis Based on International Market Power

Do China＇s silk products only have advantage in number but no pricing power in international market？ In this paper, we used the residual demand elasticity model to estimate the international market power of China＇s silk products. The empirical results revealed that China＇s raw material products such as natural silk products and semi-finished products such as satin products had certain market power in the main export markets, but the finished silk products such as woman＇s blouse or shirts and shawls had no market power in the target markets including USA and Germany. The scale economy from resource endowment and great market share are the base of the international market power of natural silk products. The advantage from industry agglomeration and great market share are the source of the international market power of satin products. Technical bottlenecks and inefficiency in brand building are the cause of unobvious international market power of China＇s finished silk products, and the competition from Italy and France has increased the difficulty to enhance market power. In order to consolidate and improve the international market power of China＇s silk products, it is suggested to stabilize the production scale and strengthen industrial base, to speed up the resources integration and optimize the industrial distribution, to strengthen science and technology innovation and adjust product structure, to speed up the brand construction and enhance the influence of brand, and to enlarge the scale of organization and achieve scale economies.

Modeling Freight Truck Trips in Birmingham Using Tour-Based Approach

This research study explores the use of an innovative freight tour-based approach to model truck trips as an alternative to the conventional trip-based approach. The tour-based approach is more realistic as it captures the intermediate stops of each truck and reflects the implications of those stops on vehicle miles traveled (VMT). The paper describes the truck tour-based model concept, and presents the framework of a truck tour-based travel demand forecasting approach. As a case study, Global Positioning System (GPS) truck data are used to determine origin, destination, and truck stops for trucks moving within the Birmingham, Alabama region. Such information is then utilized to model truck movements within the study region as individual truck tours. The tour-based model is ran, and the resulting performance measures are contrasted to those obtained from the conventional trip-based planning model used by the Regional Planning Commission of Greater Birmingham (RPCGB). This case study demonstrates the feasibility of using a tour-based freight demand forecasting model as an alternative to the conventional 4-step process currently used to estimate truck trips in the Birmingham region. The results and lessons learned from the Birmingham case study are expected to improve truck movement modeling practices in the region and advance the accuracy of truck travel demand forecasting models at other locations in the future.

Chloramine demand estimation using surrogate chemical and microbiological parameters

A model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method.The model is based on organic character（specific ultraviolet absorbance（SUVA）） of the water samples and a laboratory measure of the microbiological（Fm） decay of chloramine.The applicability of the model for estimation of chloramine residual（and hence chloramine demand） was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data.Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems.To elucidate the loss of chloramine over the wide variation of water quality used in this study,the model incorporates both the fast and slow chloramine decay pathways.The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed.It was found that with the same water source,the kinetic parameters remain the same.This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection.

A Primary Analysis of Car Model Demands In China

According to Chinese national auto standard GB3730.1 - 88, cars are classified as 5 grades by engine displacement, i.e. mini car, subcom-pact car, compact car, intermediate car and limousine.

Fragility assessment of tunnels in soft soils using artificial neural networks

Recent earthquakes have shown that tunnels are prone to damage,posing a major threat to safety and having major cascading and socioeconomic impacts.Therefore,reliable models are needed for the seismic fragility assessment of underground structures and the quantitative evaluation of expected losses.Based on previous researches,this paper presented a probabilistic framework based on an artificial neural network(ANN),aiming at the development of fragility curves for circular tunnels in soft soils.Initially,a two-dimensional incremental dynamic analysis of the nonlinear soil-tunnel system was performed to estimate the response of the tunnel under ground shaking.The effects of soil-structure-interaction and the ground motion characteristics on the seismic response and the fragility of tunnels were adequately considered within the proposed framework.An ANN was employed to develop a probabilistic seismic demand model,and its results were compared with the traditional linear regression models.Fragility curves were generated for various damage states,accounting for the associated uncertainties.The results indicate that the proposed ANN-based probabilistic framework can results in reliable fragility models,having similar capabilities as the traditional approaches,and a lower computational cost is required.The proposed fragility models can be adopted for the risk analysis of typical circular tunnel in soft soils subjected to seismic loading,and they are expected to facilitate decision-making and risk management toward more resilient transport infrastructure.

Exploring the impact of a coordinated variable speed limit control on congestion distribution in freeway

Over the past few decades, urban freeway congestion has been highly recognized as a serious and worsening traffic problem in the world. To relieve freeway congestion, several active traffic and demand management （ATDM） methods have been developed. Among them, variable speed limit （VSL） aims at regulating freeway mainline flow upstream to meet existing capacity and to harmonize vehicle speed. However, congestion may still be inevitable even with VSL implemented due to extremely high demand in actual practice. This study modified an existing VSL strategy by adding a new local constraint to suggest an achievable speed limit during the control period. As a queue is a product of the congestion phenomenon in freeway, the incentives of a queue build-up in the applied coordinated VSL control situation were analyzed. Considering a congestion occurrence （a queue build-up） characterized by a sudden and sharp speed drop, speed contours were utilized to demonstrate the congestion distribution over a whole freeway network in various sce- narios. Finally, congestion distributions found in both VSL control and non-VS control situations for various scenarios were investigated to explore the impact of the applied coordinated VSL control on the congestion distribution. An authentic stretch of V^hitemud Drive （I~~ID）, an urban freeway corridor in Edmonton, Alberta, Canada, was employed to implement this modified coordinated VSL control strategy; and a calibrated micro-simu- lation VISSIM model （model functions） was applied as the substitute of the real-world traffic system to test the above mentioned performance. The exploration task in this study can lay the groundwork for future research on how to improve the presented VSL control strategy for achieving the congestion mitigation effect on freeway.