Proceedings of Intelligent Computing and Technologies Conference最新文献_第3页

Bodo Resources for NLP - An Overview of Existing Primary Resources for Bodo 用于NLP的Bodo资源- Bodo现有主要资源的概述

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.12

Mwnthai Narzary, Gwmsrang Muchahary, Maharaj Brahma, Sanjib Narzary, P. Singh, Apurbalal Senapati

引用次数: 2

Technical Domain Classification of Bangla Text using BERT 基于BERT的孟加拉语文本技术领域分类

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.16

Koyel Ghosh, Apurbalal Senapati

引用次数: 1

Preserving Cultural Heritage with Mobile Augmented Reality – A survey 利用移动增强现实技术保护文化遗产——一项调查

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.2

Mrityunjoy Midya, R. Maity

引用次数: 0

Instagram Image Filtration with Computer Vision Instagram图像过滤与计算机视觉

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.22

Tanjimul Ahad Asif, B. Saha

引用次数: 0

Application of Artificial Neural Network to Predict TDS Concentrations of the River Thamirabarani, India 应用人工神经网络预测印度Thamirabarani河TDS浓度

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.6

T. Esakkimuthu, M. Abraham, S. Akila

{"title":"Application of Artificial Neural Network to Predict TDS Concentrations of the River Thamirabarani, India","authors":"T. Esakkimuthu, M. Abraham, S. Akila","doi":"10.21467/proceedings.115.6","DOIUrl":"https://doi.org/10.21467/proceedings.115.6","url":null,"abstract":"River water quality modeling is of prime importance in predicting the health of the rivers and in turn warns the human society about the future possibility of water problem in that area. Total dissolved solids is a prominent parameter used to access the quality of the river water. In our current study, artificial neural networking models have been developed to predict the concentrations of total dissolved solids of the river Thamirabarani in India. Neural Network toolbox of the MATLAB 2017 application was used to create and train the models. Monthly data from year 2016 to 2019 at four different sites near Thamirabarani river were procured from Tamilnadu pollution control board. Many artificial neural network architectures were built and the best performing architecture was selected for this study. With several parameters such as pH, chloride, turbidity, hardness, dissolved oxygen as input and the total dissolved solids as output parameter, the model was trained for many iterations and a final architecture was arrived which predicts the futuristic TDS concentrations of Thamirabarani in a more accurate manner. The predicted and the expected values were very close to each other. The root mean square error (RMSE) values for the selected stations such as Papanasam, Cheranmahadevi, Tirunelveli and Punnaikayal were 0.565, 0.591, 0.648 and 0.67 respectively.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116211633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0