[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120329-en":3,"doc-seo-120329-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120329,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Water Quality Analysis and Prediction using Machine Learning Algorithms","This work measures water quality by leveraging machine learning algorithms built around a Water Quality Index (WQI). Water quality parameters including temperature, dissolved oxygen (DO % sat), pH, conductivity, biochemical oxygen demand (BOD), nitrates (NO3), faecal and total coli forms (TC) are used as feature vectors. Five classification methods—Naive Bayes, Decision Tree, K-Nearest Neighbor, Support Vector Machine, and Random Forest—are applied to predict the water quality class. Experiments use a real dataset from Tamil Nadu and a synthetic dataset generated from parameter-based random sampling. Results indicate that Random Forest achieves the strongest performance and supports accurate prediction of WQI.","International Journal of Innovative Research in Science  \nEngineering and Technology (IJIRSET)  \n(A Monthly, Peer Reviewed, Refereed, Scholarly Indexed, Open Access Journal)  \nImpact Factor: 8.699 Volume 14, Issue 4 , April 2025  \nWater Quality Analysis and Prediction using Machine Learning Algorithms  \nM.Niharika, P.Naveetha, V.Devanath  \nAssociate professor, Department ofCSE, Scient Institute of Technology, Ibrahimpatnm, R.R Dist, Telangana, India  \nB.Tech Student, Department ofCSE, Scient Institute of Technology, Ibrahimpatnm, R.R Dist, Telangana, India  \nB.Tech Student, Department ofCSE, Scient Institute of Technology, Ibrahimpatnm, R.R Dist, Telangana, India  \nABSTRACT: The main objective of this work is to measure water quality using machine learning algorithms. A Water Quality Index (WQI) is a numeric expression used to evaluate the quality of a given water body. In this paper the following water quality parameters were used to evaluate the overall water quality in terms of the WQI. These parameters were as temp, dissolved oxygen (DO) (% sat), pH, conductivity, Biochemical oxygen demand (BOD), nitrates (NO3), faecal and total coli forms (TC). These parameters are used as feature vector to represent the water quality. In paper five kinds of classification algorithms, namely Navie Bayes(NB), Decision Tree(DT), K-Nearest Neighbor (KNN), Support Vector Machine(SVM), and Random Forest(RF) were employed to predict the water quality class. Experiments were conducted using the real dataset containing the details from various places in Tamil Nadu as well as the synthetic dataset generated on the basis of parameters randomly. Based on the performance of five kinds ofclassifier, it was found out that the Random Forest classifier achieves some improved result compared to other classifiers. From the analysis it shows that machine learning techniques have the good ability to predict the water quality index  \nKEYWORDS: Water Quality Index, Water Quality parameters, Data mining, Classification.  \nI. INTRODUCTION  \nThe analysis of water quality is compound problem due to the various factors influence in it. In particular, this concept is intrinsically tied to the different intended uses of the water .different uses require different criteria. Lot of research works going on the prediction of water quality. Normally water quality must be defined based on a set of physical and chemical variables that are closely related to the water’s intended use. For each variable, acceptable and unacceptable values must then be defined. Water whose variables meet the pre-established standards for a given use is considered suitable for that use. If the water fails to meet these standards, it must be treated before use. Many physical and chemical characteristics can be used to evaluate water quality or the degree of water pollution. Therefore, it is not possible in practice to clearly define water quality either on a spatial or temporal basis by separately examining the behaviour of every individual variable. The alternative, which is also difficult, consists of integrating the values of a set of physical and chemical variables into a unique value (i.e., an overall or global index). A water quality index is defined as a quality index for any use of water by simply determining the specifications required by that use. This indicator included various physical and chemical characteristics. For each variable, the index included a quality value function (generally linear) that expressed the equivalence between the variable and its quality level. These functions were defined using direct measurements of the concentration of a substance or the value of a physical variable obtained through analyses of water samples. The main theme of this paper is to make an analysis of water quality predication using machine learning algorithms with eight kind of parameters such as Ttemperature (Temp), Dissolved Oxygen (DO) (% sat), pH, conductivity, Biochemical oxygen demand (BO","cbCaikKi9K1TcOLf","https://ap.wps.com/l/cbCaikKi9K1TcOLf","pdf",2099117,1,12,"English","en",105,"# Abstract\n# Introduction\n# Related Work","[{\"question\":\"What is the main goal of the study on water quality?\",\"answer\":\"To analyze and predict water quality using machine learning algorithms based on a Water Quality Index (WQI).\"},{\"question\":\"Which water quality parameters are used as model features?\",\"answer\":\"Temperature, dissolved oxygen (DO % sat), pH, conductivity, BOD, nitrates (NO3), faecal coli forms, and total coli forms (TC).\"},{\"question\":\"Which classification algorithm performs best in predicting water quality classes?\",\"answer\":\"The Random Forest classifier achieves improved results compared with the other tested algorithms.\"}]","Water Quality Analysis and Prediction using Machine Learning Algorithms | PDF",1785729492,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"water-quality-analysis-and-prediction-using-machine-learning-algorithms","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/water-quality-analysis-and-prediction-using-machine-learning-algorithms/120329/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main goal of the study on water quality?","Question",{"text":75,"@type":76},"To analyze and predict water quality using machine learning algorithms based on a Water Quality Index (WQI).","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which water quality parameters are used as model features?",{"text":80,"@type":76},"Temperature, dissolved oxygen (DO % sat), pH, conductivity, BOD, nitrates (NO3), faecal coli forms, and total coli forms (TC).",{"name":82,"@type":73,"acceptedAnswer":83},"Which classification algorithm performs best in predicting water quality classes?",{"text":84,"@type":76},"The Random Forest classifier achieves improved results compared with the other tested algorithms.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":29,"slug":121},"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]