Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with an building and using of monolithic fuzzy based system (a TSK-FIS) to recognize realworld events and to classify these events into several catego...

Abstract This research focuses on the performance of obstacle avoidance feature implemented a wheeled mobile robot by using Sugeno Fuzzy Inference System (FIS). The test was done simulation software Webots and layout first draft out walls, floors, objects in order to set boundary obstacles for simulation. To effectiveness efficiency terms time distance, trajectory Khepera implementing FIS recor...

The aim of this study is to employ the novel Adaptive Network-based Fuzzy Inference System to optimize the torque applied on the knee link of a rehabilitation robot. Given the special conditions of stroke or spinal cord injury patients, devices with minimum error are required for performing the rehabilitation exercises. After examining the anthropometric data tables of human body, parameters su...

Performance Appraisal is the systematic assessment of performance of employees to understand the abilities for further development. According to sixth pay commission the approach adopted for evaluation of teaching staff performance focuses on areas like Teaching, Learning, Extension, Research, Publication etc. which are actually fuzzy concepts that can be captured in fuzzy terms. In the propose...

Emotion recognition plays an effective and important role in Human–Computer Interaction (HCI). Recently, various approaches to emotion recognition have been proposed in the literature, but they do not provide a powerful approach to recognize emotions from Partially Occluded Facial Images. In this paper, we propose a new method for Emotion Recognition from Facial Expression using Fuzzy Inference...

In this paper a new fuzzy method for 2D texture classification is proposed. A fuzzy rule base system is designed based on computed Geometric Moments (GMs), which are rotation, scale and translation invariant, for each texture class. Although GMs are applied to classify texture, utilizing fuzzy inference system (FIS) to make decision, develops much more robust classifier. Where GMs are inputs an...

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with building and using monolithic fuzzy-based systems (a TSK-FIS) to recognize real-world events and to classify these events into several categories...

Phishing attacks has been growing rapidly in the past few years. As a result, a number of approaches have been proposed to address the problem. Despite various approaches proposed such as feature-based and blacklist-based via machine learning techniques, there is still a lack of accuracy and real-time solution. Most approaches applying machine learning techniques requires that parameters are tu...

In this paper the development of a model for Mamdani type fuzzy rule-based systems using the new concept of granular computing (GrC) is presented. In this study a GrC algorithm is used to capture the required information in the form of data granules within a high dimensional complex database. The initial collection of information granules is used as a rule-base for a fuzzy inference system (FIS...