Neural Network-Based Data Mining Techniques for Steel Making

2003 ◽  
Author(s):  
Ravindra Sarma ◽  
Amar Gupta ◽  
Sanjeev Vadhavkar
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Data Mining Techniques ◽  
Steel Making

scholarly journals Chinese Language Feature Analysis Based on Multilayer Self-Organizing Neural Network and Data Mining Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiujin Yu ◽  
Shengfu Liu ◽  
Hui Zhang
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Feature Recognition ◽  
High Efficiency ◽  
Chinese Language ◽  
Strong Support ◽  
Superior Performance ◽  
Feature Analysis ◽  
Data Mining Techniques ◽  
Self Organizing

As one of the oldest languages in the world, Chinese has a long cultural history and unique language charm. The multilayer self-organizing neural network and data mining techniques have been widely used and can achieve high-precision prediction in different fields. However, they are hardly applied to Chinese language feature analysis. In order to accurately analyze the characteristics of Chinese language, this paper uses the multilayer self-organizing neural network and the corresponding data mining technology for feature recognition and then compared it with other different types of neural network algorithms. The results show that the multilayer self-organizing neural network can make the accuracy, recall, and F1 score of feature recognition reach 68.69%, 80.21%, and 70.19%, respectively, when there are many samples. Under the influence of strong noise, it keeps high efficiency of feature analysis. This shows that the multilayer self-organizing neural network has superior performance and can provide strong support for Chinese language feature analysis.

scholarly journals Data Mining Techniques for Identification and Classification of Various Diseases in Plants

2019 ◽  
Vol 9 (2S) ◽  
pp. 676-680
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Nearest Neighbors ◽  
Crop Productivity ◽  
Vital Role ◽  
Support Vector ◽  
Data Sets ◽  
K Nearest Neighbors ◽  
Data Mining Techniques

Data mining is currently being used in various applications; In research community it plays a vital role. This paper specify about data mining techniques for the preprocessing and classification of various disease in plants. Since various plants has different diseases based on that each of them has different data sets and different objectives for knowledge discovery. Data Mining Techniques applied on plants that it helps in segmentation and classification of diseased plants, it avoids Oral Inspection and helps to increase in crop productivity. This paper provides various classification techniques Such as K-Nearest Neighbors, Support Vector Machine, Principle component Analysis, Neural Network. Thus among various techniques neural network is effective for disease detection in plants.

scholarly journals Applying Data Mining Techniques on Continuous Sensed Data for Daily Living Activity Recognition

2015 ◽  
Vol 738-739 ◽  
pp. 191-196
Author(s):  
Yun Jie Li ◽  
Hui Song
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Decision Tree ◽  
Daily Living ◽  
Tree Model ◽  
Data Set ◽  
Data Mining Techniques ◽  
Daily Living Activity ◽  
The Neural Network ◽  
Better Than

In this paper, several data mining techniques were discussed and analyzed in order to achieve the objective of human daily activities recognition based on a continuous sensing data set. The data mining techniques of decision tree, Naïve Bayes and Neural Network were successfully applied to the data set. The paper also proposed an idea of combining the Neural Network with the Decision Tree, the result shows that it works much better than the typical Neural Network and the typical Decision Tree model.

scholarly journals Application of intellectual data analysis methods for digital educational platform

2020 ◽  
pp. 1-5
Author(s):  
Kristina Zhatkina ◽  
Oksana Kreider
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Data Analysis ◽  
Educational Services ◽  
Data Mining Techniques ◽  
Analysis Methods ◽  
The Neural Network ◽  
Competency Based ◽  
Using Data ◽  
Data Analysis Methods

This article describes the possibility of using data mining techniques. In order to join new carpet participants, it is necessary to understand that the system of interaction with them is public educational services. To implement digital educational platforms, it is proposed to create an agent that collects information about sites, and also selects and tests the architecture of the neural network to build an individual trajectory that is trained using the competency-based model.

scholarly journals PREDICTIVE MODELING OF TECHNOLOGICAL DEVELOPMENT TRENDS

2020 ◽  
Vol 55 ◽  
pp. 103-108
Author(s):  
Alla G. Kravets ◽  
◽  
Natalia A. Salnikova ◽  
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Predictive Modeling ◽  
Technological Development ◽  
Data Sources ◽  
Development Trends ◽  
Data Mining Techniques ◽  
The Neural Network ◽  
Existing Data

In the work, the problem of forecasting technological development trends was considered. A review of the sources of the global patent space, an analysis of technological development trends, a survey of data sources for training the neural network were carried out. Existing data mining techniques were analyzed for more accurate and faster forecasting. A module for predictive modeling of trends in technological development was developed, algorithms for the module for predictive modeling of trends in technological development were described.

scholarly journals AN EVALUATION OF SWINE FLU (INFLUENZA A H3N2V) VIRUS PREDICTION USING DATA MINING AND CONVENTIONAL NEURAL NETWORK TECHNIQUES

2021 ◽  
Vol 12 (4) ◽  
pp. 1377-1386
Author(s):  
Pilla Srinivas, Et. al.
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Influenza A ◽  
Medical Patient ◽  
Swine Flu ◽  
Research Trend ◽  
Data Mining Technique ◽  
Data Mining Techniques ◽  
Healthcare Data ◽  
Using Data

Nowadays, The health care commercial enterprise collects huge amounts of healthcare data which, unfortunately, are not “mined” to discover hidden information. Data mining plays a significant role in predicting diseases. The database report of medical patient is not more efficient, currently we made an Endeavour to detect the most widely spread disease in all over the world named Swine flu. Swine flu is a respiratory disease which has Numeral number of tests must be requisite from the patient for detecting a disease. Advanced data mining techniques gives us help to remedy this situation. In this work we describes about a prototype using data mining techniques, namely Naive Bayes Classifier. The Data mining is an emerging research trend which helps in finding accurate solutions in many fields. This paper highlights the various data mining technique and Convolution Neural Network used for predicting swine flu diseases.

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