No abstract

Agriculture is the important part of any developing country. As population increases the food requirement also be increases so the traditional farming not sufficient to fulfill the requirement of food. The development of industries, decreases in land space, insufficient rainfall, chemicals used in farming and peoples are moving towards the urban cities are the challenges of the agricultural field. So we have to use another source of food which we called as hydroponics. In hydroponics we can developed our plant by supplying the nutrients through water without use of soil. In this study we had used the applicability of machine learning algorithm like support vector regression(SVR), Linear Regression, Lasso Regression, Decision Tree(DT), Ridge regression and Random forest to find the crop growth accuracy from the result we found that random forest has given the highest accuracy 95% and the performance are evaluated on various model like Decision Tree Regression having better performance on (R2=0.86), Support Vector Regression having better performance on (MAE=12.65 and RMSE= 21.31) and Lasso Regression having better performance on (MSE=4.51). The whole dataset are stored on csv file and divided into two subpart 80% data is used for training and 20% is used for testing.

This paper explains expert system which will be able to fully diagnoses and treat the diseases caused by diabetes. For example Pancreas, Thyroid and Parathyroid glands are some diseases caused by diabetes. Furthermore, the expert system will give first aids in emergency cases caused by diabetes. Since, diabetes diseases are widely spreads in the India; we chose it to be the primary target from the diabetes diseases. Our expert system is not meant to replace the human physician but using such system may be useful in cases like overcoming the problems of the shortage in human physicians and accuracy and speed in processing facts. This system can be used to help the physician in their work.