Air Pollution Analysis using Ontologies and Regression Models

Rapidly throughout the world economy, "the expansive Web" in the "world" explosive growth, rapidly growing market characterized by short product cycles exists and the demand for increased flexibility as well as the extensive use of a new data vision managed data society. A new socio-economic system that relies more and more on movement and allocation results in data whose daily existence, refinement, economy and adjust the exchange industry. Cooperative Engineering Co -operation and multi -disciplinary installed on people's cooperation is a good example. Semantic Web is a new form of Web content that is meaningful to computers and additional approved another example. Communication, vision sharing and exchanging data Society's are new commercial bet. Urban air pollution modeling and data processing techniques need elevated Association. Artificial intelligence in countless ways and breakthrough technologies can solve environmental problems from uneven offers. A method for data to formal ontology means a true meaning and lack of ambiguity to allow us to portray memo. In this work we survey regression model for ontologies and air pollution.

@article{Choudhary2016,
  title     = {Air Pollution Analysis using Ontologies and Regression Models},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {7},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Parul Choudhary and Dr. Jyoti Gautam},
  doi       = {10.14569/IJACSA.2016.070723},
  url       = {https://doi.org/10.14569/IJACSA.2016.070723}
}