TRDISF_Q A Seasonal Prediction Model Integrated In RDBMS Platform For BRIHAN MUMBAI ELECTRIC SUPPLY AND TRANSPORT UNDERTKG (BEST) Mumbai

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@article{1702144,
      author = {K P Deepdarshan, Kushnappa K, Arpitha H K},
      title = {TRDISF_Q A Seasonal Prediction Model Integrated In RDBMS Platform For BRIHAN MUMBAI ELECTRIC SUPPLY AND TRANSPORT UNDERTKG (BEST) Mumbai},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {10},
      pages = {44-51},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702144.pdf},
      abstract = {The urbanization in India causes rapid rise in urban population in cities gives rise of increasing in vehicle and vehicle users. In spite of the increase in the number of travellers, the urban bus transport organizations still operate under heavy losses. This is mainly due to non-availability of right information at the right moment on various aspects of operation and functioning of public transport systems. The present work deals with the development of a seasonal prediction module for BEST public transportation. In this the specific databases for bus transport management is first designed, then developing a module for data retrieval and displaying by seasonal variation. This seasonal prediction model integrated in RDBMS platform for BRIHAN MUMBAI ELECTRIC SUPPLY AND TRANSPORT UNDERTKG(BEST) Mumbai is effectively used by transportation engineers to take right decision at right time to manage the public transportation in high profit.},
      keywords = {BEST, DSS, Entity relationship,TRDISF_Q, Regression analysis, SPSS},
      month = {April},
  }