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Full-Text Articles in Mathematics
Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.
Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.
Doctoral Theses
Evolutionary Algorithms (EAs) for Many-Objective Optimization (MaOO) problems are challenging in nature due to the requirement of large population size, difficulty in maintaining the selection pressure towards global optima and inability of accurate visualization of high-dimensional Pareto-optimal Set (in decision space) and Pareto-Front (in objective space). The quality of the estimated set of Pareto-optimal solutions, resulting from the EAs for MaOO problems, is assessed in terms of proximity to the true surface (convergence) and uniformity and coverage of the estimated set over the true surface (diversity). With more number of objectives, the challenges become more profound. Thus, better strategies have …
Some Issues In Unsupervised Feature Selection Using Similarity., Partha Pratim Kundu Dr.
Some Issues In Unsupervised Feature Selection Using Similarity., Partha Pratim Kundu Dr.
Doctoral Theses
Pattern recognition is what humans do most of the time, without any conscious effort, and fortunately excel in. Information is received through various sensory organs, processed simultaneously in the brain, and its source is instantaneously identified without any perceptible effort. The interesting issue is that recognition occurs even under non-ideal conditions, i.e., when information is vague, imprecise or incomplete. In reality, most human activities depend on the success in performing various pattern recognition tasks. Let us consider an example. Before boarding a train or bus, we first select the appropriate one by identifying either the route number or its destination …
On Supervised And Unsupervised Methodologies For Mining Of Text Data., Tanmay Basu Dr.
On Supervised And Unsupervised Methodologies For Mining Of Text Data., Tanmay Basu Dr.
Doctoral Theses
The supervised and unsupervised methodologies of text mining using the plain text data of English language have been discussed. Some new supervised and unsupervised methodologies have been developed for effective mining of the text data after successfully overcoming some limitations of the existing techniques.The problems of unsupervised techniques of text mining, i.e., document clustering methods are addressed. A new similarity measure between documents has been designed to improve the accuracy of measuring the content similarity between documents. Further, a hierarchical document clustering technique is designed using this similarity measure. The main significance of the clustering algorithm is that the number …
Single And Multiobjective Approaches To Clustering With Point Symmetry., Sriparna Saha Dr.
Single And Multiobjective Approaches To Clustering With Point Symmetry., Sriparna Saha Dr.
Doctoral Theses
In our every day life, we make decisions consciously or unconsciously. This decision can be very simple such as selecting the color of dress or deciding the menu for lunch, or may be as difficult as those involved in designing a missile or in selecting a career. The former decision is easy to take, while the latter one might take several years due to the level of complexity involved in it. The main goal of most kinds of decision-making is to optimize one or more criteria in order to achieve the desired result. In other words, problems related to optimization …
Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr.
Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr.
Doctoral Theses
No abstract provided.
Feature Evaluation, Classification And Rule Generation Using Fuzzy Sets And Neural Networks., Rajat Kumar De Dr.
Feature Evaluation, Classification And Rule Generation Using Fuzzy Sets And Neural Networks., Rajat Kumar De Dr.
Doctoral Theses
Pattern recognition and machine learning form a major area of research and develop- ment activity that encompasses the processing of pictorial and other non-numerical information obtained from the interaction between science, technology and society. A motivation for the spurt of activity in this field is the need for people to com- municate with the computing machines in their natural mode of communication. Another important motivation is that the scientists are also concerned with the idea of designing and making intelligent machines that can carry out certain tasks that we human beings do. The most salient outcome of these is the …
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Doctoral Theses
Machine recognition [1, 2] of patterns can be viewed as a two-fold task, consisting of learning the invariant and common properties of a set of samples characterizing a class, and of deciding a new sample as a possible member of the class by noting that it has properties common to those of the set of samples. In other words, pattern recognition by computers can be described as a transformation from the measurenment space M to the feature space F and finally to the decision space D (1), i.e., M ⟶F⟶D.Here, the mapping 6 : F⟶D is the decision function and …
Multivalued Approach For Uncertainty Management., Deba Prasad Mandal Dr.
Multivalued Approach For Uncertainty Management., Deba Prasad Mandal Dr.
Doctoral Theses
Real life problems are rarely free from uncertainty which usually emerges from the deficiencies of information available from a situation. The defi- ciencies may result from incomplete, imprecise, not fully reliable, vague or contradictory information depending on the problem. Management of uncer- tainty in a decision making system has been an important research problem for many years.Until the inception of the concept of fuzzy set theory in 1965 (1), the theory of probability and statistics was the primary mathematical tool for modeling uncertainty in a system/situation. Fuzzy set theory has shown enormous proinise in handling uncertaintics to a reasonable extent …
On Image Information Measures And Object Extraction., Nikhil Ranjan Pal Dr.
On Image Information Measures And Object Extraction., Nikhil Ranjan Pal Dr.
Doctoral Theses
The field of image processing deals with the manipulation of data which are inherently two-dimensional in nature. techniques of image processing sten from two principal application The areas, namely, Improvement of pictorial information for human interpretation and processing of scene data for automatic machine perception. These areas together have experienced a vigorous growth in recent years because they have offered a number of important applications in solving scientific and engineering problems. In biological and medical sciences, we are interested in automatie analysis and interpretation of radiographs, cell images micrographs. In netallurgical, geological and and tissue environmental sciences, we are concerned …
On Consisten Estimation Of Classes In R2 In The Context Of Cluster Analysis., C. A. Murthy Dr.
On Consisten Estimation Of Classes In R2 In The Context Of Cluster Analysis., C. A. Murthy Dr.
Doctoral Theses
Brief reviow of oluater analysis. The literature on oluater analy ste is baaically orianted touerda the development of algori thme 1,2,3, 4, 5]. Andaxberg [1] gives the verloue stepo in aluster analy al a starting from the chai ce of data pointa to interpreting the results. Harti gan 5] desoribes veari oun cluatering algo- ri thms in hin book. He also states the ueos of tho ae methoda in vari oue fielde. Jardines end Sibaon [6] dovelopa meaoures of di ssimilarity and regerde a alustor mothod as a funotion from di andmilori tymatrlces to trees. Clustering tochniquos can ba broadly …