Available parking space occupancy change characteristics and short-term forecasting model

Based on an available parking space occupancy （APSO） survey conducted in Nanjing, China, an APSO forecasting model is proposed. The APSO survey results indicate that the time series of APSO with different time-sections are periodical and self-similar, and the fluctuation of the APSO increases with the decrease in time-sections. Taking the short-time change behavior into account, an APSO forecasting model combined wavelet analysis and a weighted Markov chain is presented. In this model, an original APSO time series is first decomposed by wavelet analysis, and the results include low frequency signals representing the basic trends of APSO and several high frequency signals representing disturbances of the APSO. Then different Markov models are used to forecast the changes of low and high frequency signals, respectively. Finally, integrating the predicted results induces the final forecasted APSO. A case study verifies the applicability of the proposed model. The comparisons between measured and forecasted results show that the model is a competent model and its accuracy relies on real-time update of the APSO database.

Forecasting available parking space with largest Lyapunov exponents method

The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.

Stereo garage parking space allocation model and simulation analysis

Based on grey neural network and particle swarm optimization algorithm,an automated stereo garage decision model is proposed to solve the problems of long waiting queue and low efficiency of automated parking garage.The gray neural network is used to forecast the stay time of the vehicle and particle swarm optimization algorithm is used to allocate the parking spaces in the stereo garage.The proposed stereo garage mathematical model is established on condition that vehicle arrival interval obeys Poisson distribution.The performance of stereo garage is evaluated by the average waiting time,average waiting queue length,average service time and average energy consumption of the customers.By comparing the efficiency indexes of the existing model based on near-distribution principle and the proposed model based on gray neural network and particle swarm algorithm,it is proved that the proposed model based on gray neural network and particle swarm algorithm is effective in improving the efficiency of garage operation and reducing the energy consumption of garage.

About the Optimized Design of the Parking Space on the Campus of a College

In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. Taking Baoding College as an example, this article analyzes the current situation of static traffic on campus and finds out the problem of parking on campus through questionnaire surveys and field surveys. Analyze the growth trend of the number of motor vehicles based on the data, use the GM (1, 1) model and the linear fitting model to predict the number of motor vehicles in the future, and determine the size and layout of the parking lot based on the campus size, functional zoning, and road layout. The big campus-based parking system planning method based on big data can effectively solve the problems of small sample data, low accuracy, and poor timeliness of traditional methods, which improves the practicability and scientificity of planning results.

Study on the Distribution Characteristics and Influencing Factors of Park Green Space in Wuhan City

The distribution characteristics of park green space in Wuhan City were studied by standard deviation ellipse(SDE)method,average nearest neighbor index,kernel density estimation(KDE)method and scale index method.At the same time,the influencing factors of its distribution were discussed from three aspects of nature,social economy and culture with a geographical detector.The results show that(1)the distribution of park green space in Wuhan was relatively concentrated,and the directionality was not strong.The distribution mode was clustered mode.There were four main aggregation centers,which were located in Jianghan District,Qingshan District,Dongxihu District and Wuchang District respectively.Among them,the scale index of Jianghan District was the highest,up to 0.5902,while that of Xinzhou district was the lowest,only 0.0047.(2)The order of interpretation intensity of park green space distribution in Wuhan was population density(0.382)>regional GDP(0.278)>location of historical relics(0.165)>urbanization rate(0.136)>watershed zoning(0.069)>altitude(0.012).(3)The interaction of population density and watershed zoning had the strongest explanation for the distribution of park green space in Wuhan.Except for the influence of population density,the interaction of urbanization rate and regional GDP had the strongest explanation for the distribution of park green space in Wuhan.

Parking Availability Prediction with Coarse-Grained Human Mobility Data

Nowadays,the anticipation of parking-space demand is an instrumental service in order to reduce traffic congestion levels in urban spaces.The purpose of our work is to study,design and develop a parking-availability predictor that extracts the knowledge from human mobility data,based on the anonymized human displacements of an urban area,and also from weather conditions.Most of the existing solutions for this prediction take as contextual data the current road-traffic state defined at very high temporal or spatial resolution.However,access to this type of fine-grained location data is usually quite limited due to several economic or privacy-related restrictions.To overcome this limitation,our proposal uses urban areas that are defined at very low spatial and temporal resolution.We conducted several experiments using three Artificial Neural Networks:Multilayer Perceptron,Gated Recurrent Units and bidirectional Long Short Term Memory networks and we tested their suitability using different combinations of inputs.Several metrics are provided for the sake of comparison within our study and between other studies.The solution has been evaluated in a real-world testbed in the city of Murcia(Spain)integrating an open human-mobility dataset showing high accuracy.A MAPE between 4%and 10%was reported in horizons of 1 to 3 h.

Balanced Consideration of Urban Park Green Space to Provide Services and Disservices

Ecosystem services(ES),the benefits of ecosystem function and structure to human well⁃being,have been receiving continued attention from international community since the publication of the millennium ecosystem assessment(MA).While humans enjoy all kinds of services provided by the ecosystem,they are also adversely affected by the services provided by the ecosystem,which are called ecosystem disservices(EDS).Based on EDS related research,this paper expounds the EDS concept and connotation to urban park green space as the research object,defines the concept and classification of urban park green space ecosystem disservices(PEDS),and introduces the influencing factors of the listed examples of urban PEDSs.It also discusses equilibrium relationship of the urban park green space service and disservice,and summarizes the research on urban PEDS to improve the meaning of human well⁃being.Finally,it points out the factors that should be considered in the planning,design,management,and maintenance of future urban park green space.

Research on Micro Technology of Microclimate Environment in Urban Green Space Based on Humanization Concept

To create a comfortable microclimate environment,the design methods of green layout and green structure of four common forms of urban green space(park green space,road green space,waterfront open green space,and green space between houses)were discussed,and the modes"concentric three rings"and"three-layer sandwich cake",as well as the matching principles of three-dimensional green elements of trees and shrubs with lawn and hard matrix elements,were proposed.

Hainan Space Theme Park

Hainan Space Theme Park is a key project for the construction of Hainan international tourism island, and an associated project

The Scale-Effects of Different Land Use Types on the Distribution Pattern of Park Green Space at Multiple Grid Scales-A Case Study on the Main Urban Area of Nanjing,China

Exploring the scale-effect of different land use types on the distribution pattern of urban park green space(PGS)at multiple grid scales would inform rational allocation and efficient collaborative construction of urban development land at different scales.Selecting 300-m,500-m,1,000-m,and 2,000-m grid scales,the research employed Create Fishnet tool in ArcGIS and Geodetector to construct a scale-effect analysis framework that revealed the scale-effects of different land use types on the distribution pattern of PGS at multiple grid scales in the main urban area of Nanjing,China in 2006,2012,and 2017.Main research results are:1)the overall distribution pattern of PGS showed the evolution characteristics from polarization to advancing quality and efficiency,while the trend gradually weakened with the increase of grid scale;2)the scale-effect of other land use types on PGS increasingly enhanced-the larger the grid scale,the more obvious the synergistic or compressive effect;3)the interactive scaleeffects of different land use types gradually enhanced-the larger the grid scale,the more significant the overall factor interaction;and 4)at the 300-m grid scale,the major interaction factors were residential,transportation,industrial/manufacturing,water area,and administration/public services,which gradually changed to residential,water area,and administration/public services up to the 2,000-m grid scale.The findings of this paper are expected to deepen the theory of the coupling between PGS and other land use types,as well as provide scientific support and a basis for efficient allocation,spatial layout optimization,and sustainable development of urban spaces.

Improved CS Algorithm and its Application in Parking Space Prediction

This paper simulates the cuckoo incubation process and flight path to optimize the Wavelet Neural Network(WNN)model,and proposes a parking prediction algorithm based on WNN and improved Cuckoo Search(CS)algorithm.First,the initialization parameters are provided to optimize the WNN using the improved CS.The traditional CS algorithm adopts the strategy of overall update and evaluation,but does not consider its own information,so the convergence speed is very slow.The proposed algorithm employs the evaluation strategy of group update,which not only retains the advantage of fast convergence of the dimension-by-dimension update evaluation strategy,but also increases the mutual relationship between the nests and reduces the overall running time.Then,we use the WNN model to predict parking information.The proposed algorithm is compared with six different heuristic algorithms in five experiments.The experimental results show that the proposed algorithm is superior to other algorithms in terms of running time and accuracy.

Study on Ecological Development of Urban Parks

Research background,significance,characteristics and planning methods of the ecological development of urban parks were elaborated.This paper took green space planning of Xishan Park in Qianxi City for example,explored the application of ecological development theories in green space planning of urban park.

Hangzhou Parking Problem and Underground Space Usage

The author analyses the possibility,feasibility and scheme of solving the parking problem in the city ofHangzhou by using the underground space.

A Modern Concerto of National Parks and Urban Parks:Book Review of Parkscapes:Green Spaces in Modern Japan

Parkscapes:Green Spaces in Modern Japan Author:Thomas R.H.Havens Year:2011Publisher:University of Hawai’i Press ISBN:9780824834777(288 pages,in English)Japanese classical gardens,which can be seen in the courtyards of temples,courtyards of ancient feudal landlords(emperor,general,and daimyo),and some private mansions of modern statesmen and industrialists,have a long history and are well known around the world.Even though there are many monographs