105 research outputs found
A revisited convex hull-based fuzzy linear regression model for dynamic fuzzy healthcare data
No full textHealthcare data analysis is widely used in cancer classification and disease prediction. Hence, fuzzy linear regression integration into dynamic analysis can provide better decision making process in healthcare industry especially dealing with dynamic data analysis. Healthcare officers and related researchers require efficient regression tools to produce precise inference as an aid to save human life. However, the key problem in this circumstance is related to computational complexity and processing time. Both of these parameters drastically increase beside an increment of data size in dynamic databases. With regard to the aforementioned problem, the main objective is to improve the implementation of fuzzy linear regression for fuzzy data by addressing and mitigating some limitations of the existing methods through a convex hull approach. More specifically, we look at the realization of an incremental algorithm called Beneath-Beyond algorithm. This algorithm provides a useful vehicle to reduce the computing time and computational complexity as well. Furthermore, a real fuzzy healthcare data set which derive from healthcare industry will be selected as the main source of data sets. Additionally, there are two major procedures or components namely a formulation of a product of fuzzy number optimization and the use of the convex hull technique to the obtained locus points in hyper-rectangles polygon and each of them have their own distinctive activities. As a research output, the combination of this mathematical geometry algorithm and fuzzy linear regression analysis will produce an optimized algorithm called convex hull-based fuzzy linear regression model deliberately for dynamic fuzzy healthcare data. The proposed algorithm may help to produce a rapid decision making especially for critical area such as healthcare industry
Building Dynamic Fuzzy Regression Model based on Convex Hull Algorithm and Its Industrial Applications
No full text早大学位記番号:新726
A new hybrid evolutionary algorithm with MCDM for plant forecasting using FIS
No full textLarge Indonesians are engaged in the agrarian sector, so the character of a climate and weather such as rainfall greatly affects the sustainability of its income. Climatic and weather factors are used for agricultural considerations, especially in determining the suitability of crop species to be cultivated somewhere. But the conditions of the weather often change, because the definition of weather itself covers a narrow area and at a short time, so every time will change
A Novel Idea of Real-Time Fuzzy Switching Regression Analysis: A Nuclear Power Plants Case Study
No full textDesign of Door Security System Based on Face Recognition with Arduino
Get PDFRobotics technology is very useful for the lives of many people today. Almost all aspects of his life utilize robotics technology according to the required field. The development of robotics technology has become a higher quality of human life. Perhaps robotics are still less popular among the general public who still thinks robotics are humanoid robots (robots or human machines). Robotics has been widely implemented in the real world ranging from the fields of industry, medicine, entertainment, security, to household appliances. In the field of security, robotics has an important role. As the robot principle itself is tireless and has little tolerance, the product in robotics in the security field can be a very useful tool. In addition to facilitate human insecurity, robotics products can also facilitate human in various jobs, such as in the locking doors or walls of anyone who already exists. The development of robotics is in line with the development of computer vision which is increasing its application in everyday life. With this research, is expected to improve security and comfort in the security room. The design of this system using electronic door locks, open source OpenCV and webcam as a unit component
Possibilistic regression analysis of influential factors in the planning and implementation of occupational health and safety management systems
No full text
Real-time fuzzy regression analysis: A convex hull approach
No full textIn this study, we present an enhancement of fuzzy regression analysis with regard to its aspect of real-time processing. Let us recall that fuzzy regression generalizes the concept of classical (numeric) regression in the sense of bringing additional capabilities that allow the model to deal with fuzzy (granular) data. We show that a convex hull method provides a useful vehicle to reduce computing time, which becomes of particular relevance in case of real-time data analysis. Our objective is to develop an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. In this algorithm, the re-construction of convex hull edges depends on incoming vertices while a re-computing procedure can be realized in real-time. We demonstrate the use of the developed enhancement to application to unit performance assessment and air pollution data. An important role of convex hull is contrasted with the limitations of linear programming used in the "standard" regression.Convex hull Fuzzy set Linear programming Regression analysis Fuzzy regression analysis
- …
