Abstract: With the enhanced exploration of the new generation of the web, people are free to state their opinion on any particular topic like product, services, organization and even on other people online in different social media platform and thus an innumerous amount of user generated contents are being created each moment. Hence, the need for mining this information has become the priority of the researcher so that they can identify the user’s sentiments and guide other people in various fields. Sentiment analysis deals with analyzing the review, opinion, attitude and emotions of a person from a given set of text by categorizing those on the basis of polarity as positive, negative and neutral. In this paper, sentiment of the social media text in Assamese Language is being analyzed because most of the communication is done through regional language and as a researcher from this region it is utmost concern to mine this information. To analyze the sentiments from the manually prepared datasets, LSTM- deep learning algorithm is used and implemented it in Python environment and also overall performance is measured in terms of accuracy, precision, recall and f1-score.
Abstract: With the enhanced exploration of the new generation of the web, people are free to state their opinion on any particular topic like product, services, organization and even on other people online in different social media platform and thus an innumerous amount of user generated contents are being created each moment. Hence, the need for mining this...Show More
Abstract: The Generalized Weng Model is one of the basic models for oil production forecasting. Professor Chen Yuanqian first proposed the linear iterative trial-and-error method to solve the generalized Weng Model, and scholar Zhao Lin proposed the method to solve the Weng model based on binary regression. In this paper, a new method for solving Weng Model is put forward. Taking Liaohe Oilfield in China as an example, the process and results of the three methods are compared, and the advantages and disadvantages of the three methods are analyzed. The results show that when the original linear iterative trial and error method solves the model, it needs to simulate the value of parameter b with computer software, and then select a judgment criterion to find the optimal b value. In this paper, a method based on binary regression is proposed which can directly calculate parameter b. The new method can directly calculate the parameter b better than the method based on binary regression. The method in this paper is to fit all the data at one time, avoiding the above two kinds of uncertainties, and the calculation workload is small and can be realized by EXCEL, which is convenient for technical personnel.
Abstract: The Generalized Weng Model is one of the basic models for oil production forecasting. Professor Chen Yuanqian first proposed the linear iterative trial-and-error method to solve the generalized Weng Model, and scholar Zhao Lin proposed the method to solve the Weng model based on binary regression. In this paper, a new method for solving Weng Model ...Show More