Forecasting Beijing Transportation Hub Areas’s Pedestrian Flow Using Modular Neural Network

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Forecasting Cohesionless Soil Highway Slope Displacement Using Modular Neural Network

The highway slope failures are triggered by the rainfall, namely, to create the disaster. However, forecasting the failure of highway slop is difficult because of nonlinear time dependency and seasonal effects, which affect the slope displacements. Starting from the artificial neural networks ANNs since the mid-1990s, an effective means is suggested to judge the stability of slope by forecastin...

متن کامل

Forecasting Natural Gas Demand Using Meteorological Data: Neural Network Method

The need for prediction and patterns of gas consumption especially in the cold seasons is essential for consumption management and policy planning decision making. In residential and commercial uses which account for the bulk of gas consumption in the country the effects of meteorological variables have the highest impact on consumption.  In the present research four variables include daily ave...

متن کامل

Designing Incomplete Hub Location-routing Network in Urban Transportation Problem

In this paper, a comprehensive model for hub location-routing problem is proposed which no network structure other than connectivity is imposed on backbone (i.e. network between hub nodes) and tributary networks (i.e. networks which connect non-hub nodes to hub nodes). This model is applied in public transportation, telecommunication and banking networks. In this model locating and routing is c...

متن کامل

River Flow Forecasting Using Artificial Neural Networks

River flow forecasting is required to provide basic information on a wide range of problems related to the design and operation of river systems. The availability of extended records of rainfall and other climatic data, which could be used to obtain stream flow data, initiated the practice of rainfall-runoff modelling. While conceptual or physically-based models are of importance in the underst...

متن کامل

River Flow Forecasting using Recurrent Neural Networks

Forecasting a hydrologic time series has been one of the most complicated tasks owing to the wide range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently, Artificial Neural Networks (ANNs) have become quite popular in time series forecasting in various fields. This paper demonstrates the use of ANNs to foreca...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Discrete Dynamics in Nature and Society

سال: 2015

ISSN: 1026-0226,1607-887X

DOI: 10.1155/2015/749181