Parameter estimation by type-2 fuzzy logic in case that data set has outlier

modeling loss data by phase-type distribution

بیمه گران همیشه بابت خسارات بیمه نامه های تحت پوشش خود نگران بوده و روش هایی را جستجو می کنند که بتوانند داده های خسارات گذشته را با هدف اتخاذ یک تصمیم بهینه مدل بندی نمایند. در این پژوهش توزیع های فیزتایپ در مدل بندی داده های خسارات معرفی شده که شامل استنباط آماری مربوطه و استفاده از الگوریتم em در برآورد پارامترهای توزیع است. در پایان امکان استفاده از این توزیع در مدل بندی داده های گروه بندی ...

Data-Driven Design of Type-2 Fuzzy Logic System by Merging Type-1 Fuzzy Logic Systems

Outlier Tolerant Parameter Estimation

Real world does not only provide noisy instead of perfect data. Every experimentalist has now and then to deal with outliers. The situation is simple if isolated points stick out of the general trend by a large amount. Arguments can then usually be found why such a point should be disregarded. The situation becomes critical if the outliers are not that obvious. This is usually the case for para...

Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation

predicting the effort of a successful project has been a major problem for software engineers the significance of which has led to extensive investigation in this area. One of the main objectives of software engineering society is the development of useful models to predict the costs of software product development. The absence of these activities before starting the project will lead to variou...

Type-2 fuzzy logic systems

We introduce a type-2 fuzzy logic system (FLS), which can handle rule uncertainties. The implementation of this type-2 FLS involves the operations of fuzzification, inference, and output processing. We focus on “output processing,” which consists of type reduction and defuzzification. Type-reduction methods are extended versions of type-1 defuzzification methods. Type reduction captures more in...