In this paper, a fast highlight detection and scoring method is proposed using an ondemand feature extraction and a fuzzy inference system. The proposed method partitions video to highlights and analyzes their content using an on-demand feature extraction approach. Then, a score is assigned to each highlight using a Fuzzy Inference System (FIS) according to the analyzed content. The assigned sc...

This paper presents a nuclear case study, in which a fuzzy inference system (FIS) is used as alternative approach in risk analysis. The main objective of this study is to obtain an understanding of the aging process of an important nuclear power system and how it affects the overall plant safety. This approach uses the concept of a pure fuzzy logic system where the fuzzy rule base consists of a...

Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper we will study and analyze the optimal lot size in a real productio...

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM ...

The research work presented in this paper proposes a data-driven modeling method for bearings remaining useful life estimation based on Takagi-Sugeno (T-S) fuzzy inference system (FIS). This allows identifying the parameters of classic T-S FIS, starting with small quantity data. In work, we used vibration signals data from number over an entire period run-to-failure. FIS model inputs are featur...

Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...

As a scientific publishing house, Indonesian Institute of Sciences (LIPI) Press' encountered some problems in publication planning, mainly predicting the optimum production publications. This study aimed to enhance fuzzy inference system (FIS) parameters using genetic algorithm (GA). The enhancements led optimally predict number LIPI Press publications for following year. predictors used were w...

Fuzzy systems address the imprecision of the input and output variables, which formally describe notions like “rather warm” or “pretty cold”, while provide a behaviour that depends on fuzzy data. This class of systems are classically represented by means of Fuzzy Inference Systems (FIS), a computing framework based on the concepts of fuzzy if-then rules and fuzzy reasoning. Even if FIS are larg...

In this paper we presented an architecture and basic learning process underlying in fuzzy inference system and adaptive neuro fuzzy inference system which is a hybrid network implemented in framework of adaptive network. In real world computing environment, soft computing techniques including neural network, fuzzy logic algorithms have been widely used to derive an actual decision using given i...

Laser metal deposition (LMD) process is an additive manufacturing technique that has attracted the interest of automotive and aerospace industries due to its ability manufacture parts with complex geometries different types metallic materials. However, structure deposited layers geometrical characteristics manufactured are influenced by interaction among parameters. In this paper, fuzzy inferen...