Knowledge Extraction
Elham Samadi; Hasanali Bakhtiyar Nasrabadi; Zohreh Saadatmand
Abstract
The aim of this research is to employ neural networks in discovering functional knowledge based on the rational training of Avicenna and Kant. The methodology of this study is based on deep learning neural networks, making it an exploratory research. Given the practicality of functional knowledge, this ...
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The aim of this research is to employ neural networks in discovering functional knowledge based on the rational training of Avicenna and Kant. The methodology of this study is based on deep learning neural networks, making it an exploratory research. Given the practicality of functional knowledge, this research is applied in nature. To assess the significance of components and evaluation indicators of functional knowledge, text mining and the frequency of related symbols have been used. In order to utilize data mining techniques in this research, the WEKA software has been employed. The algorithms considered for implementation in this study are MLP, SVR, AdaBoost.R, Bagged Trees (BAGTREE), Linear Regression (LR), and Least Squares Support Vector Regression (LSSVR). According to the results obtained for functional knowledge, the LSSVR and SVR methods outperform the others, indicating their superiority. As the charts illustrate, there is significant volatility in this dataset, making prediction challenging. Furthermore, the R2 value is very close to one, indicating relatively accurate predictions by the methods. Neural networks can serve as powerful tools to aid in rational thinking, logical decision-making, and better understanding of the surrounding world, in line with the perspectives of Avicenna and Kant. These tools can assist in analyzing and interpreting complex data in these fields and strive for rationality and human excellence.
Knowledge Extraction
Zahra Sadafi Tehrani; Masoumeh Al-Sadat Abtahi; Ezatollah Naderi; Maryam Seif Naraghi Saif Naraghi
Abstract
The purpose of the study is to analyze the sixth grade textbooks for the application of financial knowledge from the point of view of the professors of the financial management department of public and private universities. The research method is descriptive-analytical. The statistical population of ...
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The purpose of the study is to analyze the sixth grade textbooks for the application of financial knowledge from the point of view of the professors of the financial management department of public and private universities. The research method is descriptive-analytical. The statistical population of all professors of the financial management department of public and private universities with more than 10 years of experience in Tehran province is determined to be around 322 people. A researcher-made questionnaire was used to collect data. This tool is a combination of the financial knowledge tests of the National Council of Economic Education of America and the national standards for personal finance of the Jumpstart model and adapted to the conditions of Iranian students. Professors, experts of the Department of Economics of Islamic Azad University in Tehran and experts of the Education Organization have confirmed the validity of the questionnaire and its reliability has been confirmed by calculating Cronbach's alpha of 0.894. Text mining methods (mean, percentage and frequency) and inferential statistics have been used to review and analyze the data. The results of the research show that the educational goals of the framework of the personal finance book, the framework of content and learning experiences, the framework of organizing teaching-learning experiences and the design of the evaluation framework of learning experiences in the application of financial knowledge in sixth grade textbooks are effective from the point of view of financial experts and experts.
