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An Optimized Way to Deliver Goods by Using Multilayer Artificial Neural Network Model.

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Title: An Optimized Way to Deliver Goods by Using Multilayer Artificial Neural Network Model.
Authors: Bhatnagar, Amit1, Shukla, Arvind Kumar2
Source: Turkish Online Journal of Qualitative Inquiry. 2021, Vol. 12 Issue 7, p14255-14264. 10p.
Subject Terms: Road running, Delivery of goods, Local delivery services, Automobile speed
Abstract: This paper provides way to understand the use of Multi-layer Artificial Neural Network (MANN) Model for getting vehicles flow prediction and finding optimum path to deliver goods based on the vehicles flow data during limited time period. In this manuscript, we design someMulti-layer Artificial NeuralNetwork Model with average speed of vehicles, number of vehicles running on road, time, density of vehicles, day, number of dumb vehicles on the road and many other variables as input variables. We can take some other conditions which are not used in previous studies. Several conditions will not easily predict like behavior of driver, sudden road blockage, rainy seasons, festivals demand and etc. We can observe the least density of vehicles on the road then the vehicle driver selected best predicted way for delivery of the goods. The route of vehicle is decided according to the reliable and high-quality result of Multi-layer Artificial Neural Network Model. [ABSTRACT FROM AUTHOR]
Copyright of Turkish Online Journal of Qualitative Inquiry is the property of Turkish Online Journal of Qualitative Inquiry and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
An: 161812701
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: An Optimized Way to Deliver Goods by Using Multilayer Artificial Neural Network Model.
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  Data: <searchLink fieldCode="AR" term="%22Bhatnagar%2C+Amit%22">Bhatnagar, Amit</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shukla%2C+Arvind+Kumar%22">Shukla, Arvind Kumar</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Turkish+Online+Journal+of+Qualitative+Inquiry%22">Turkish Online Journal of Qualitative Inquiry</searchLink>. 2021, Vol. 12 Issue 7, p14255-14264. 10p.
– Name: Subject
  Label: Subject Terms
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  Data: <searchLink fieldCode="DE" term="%22Road+running%22">Road running</searchLink><br /><searchLink fieldCode="DE" term="%22Delivery+of+goods%22">Delivery of goods</searchLink><br /><searchLink fieldCode="DE" term="%22Local+delivery+services%22">Local delivery services</searchLink><br /><searchLink fieldCode="DE" term="%22Automobile+speed%22">Automobile speed</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper provides way to understand the use of Multi-layer Artificial Neural Network (MANN) Model for getting vehicles flow prediction and finding optimum path to deliver goods based on the vehicles flow data during limited time period. In this manuscript, we design someMulti-layer Artificial NeuralNetwork Model with average speed of vehicles, number of vehicles running on road, time, density of vehicles, day, number of dumb vehicles on the road and many other variables as input variables. We can take some other conditions which are not used in previous studies. Several conditions will not easily predict like behavior of driver, sudden road blockage, rainy seasons, festivals demand and etc. We can observe the least density of vehicles on the road then the vehicle driver selected best predicted way for delivery of the goods. The route of vehicle is decided according to the reliable and high-quality result of Multi-layer Artificial Neural Network Model. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Turkish Online Journal of Qualitative Inquiry is the property of Turkish Online Journal of Qualitative Inquiry and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 14255
    Subjects:
      – SubjectFull: Road running
        Type: general
      – SubjectFull: Delivery of goods
        Type: general
      – SubjectFull: Local delivery services
        Type: general
      – SubjectFull: Automobile speed
        Type: general
    Titles:
      – TitleFull: An Optimized Way to Deliver Goods by Using Multilayer Artificial Neural Network Model.
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            NameFull: Bhatnagar, Amit
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            NameFull: Shukla, Arvind Kumar
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            – D: 01
              M: 08
              Text: 2021
              Type: published
              Y: 2021
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              Value: 12
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              Value: 7
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            – TitleFull: Turkish Online Journal of Qualitative Inquiry
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