درخت حوزه‌های تخصصی

Agriculture is one of the essential sources of occupation and revenue in India. Conferring to existing statistics, most agriculturalists are facing severe losses due to poor farming yield. Farming activities are challenged by various environmental factors that affect agricultural productivity to a greater extent. The present farming situation is above the average of the process involves more biochemical bases for managing the diseases and other destructing facts. The foremost problems they are facing in day-to-day farming tasks are crop or plant diseases affecting productivity. Also, the growth of weeds along with field crops has been another challenge.  The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. The result has been evaluated and observed through the performance evaluation metrics using confusion matrix, accuracy, precision, Sensitivity, specificity with the observations, research, and studies. The statistics have expressed the overall accuracy of 98% by achieving the detection of diseases in plants and by removing the weeds that ruin the growth of plants.

Purpose- Rural entrepreneurship is a suitable solution for empowerment and capacity building in rural areas in order to change the current life pattern, create economic, social, environmental and institutional equality.Meanwhile, women play apivotalrole in promoting employment and improving the economic status of rural areas.Thus, a thorough conception of all aspects of entrepreneurship can be an effective factor in increasing the success rate.Design/methodology/approach- In this research, a descriptive survey and correlation method have been used.To analyze the data collected through field study, various descriptive and inferential statistical methods have been employed by SPSS15 software.Using the LISREL 8.5 software, the relationships between independent and dependent variables as well as the structural equation have been determined.Findings- The results indicate that three factors including structural, behavioral, contextual and the most important item of each factor including "paying attention to the social environment", "paying attention to development","Legislating the necessary laws and regulations" could be measured integrally in the structural equation model, respectively.It is also revealed how is possible to create innovatively the identifying and implementing stages of the investing process and creating women's businesses by becoming more detailed and determining the subset of each of the main structural, behavioral and contextual factors.Considering the structural equation model, the importance of these factors in the investing process and creating women's businesses in the southern villages of the country is highlighted.Original/value- Research and training activities can be one of the initiatives of governments and institutions related to the subject. Knowing the market context, the experiences of other regions of the country, obstacles to women's entrepreneurship, and the opportunities for women's entrepreneurship in different rural areas of the south of the country provide suitable opportunities for women's entrepreneurial activities. Furthermore, training programs should be based on women's condition in the village in such a way that the level of education, type of profession, geographical region are of the effective factors in the design and implementation of training programs. Providing training packages and the possibility of distance training is also useful for all entrepreneurs in the southern parts of the country.