ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

A fuzzy control system which is a typical system utilizing fuzzy model is mainly using the Max-Min CRI (Compositional Rule of Inference) method by Zadeh and Mamdani for fuzzy inference. But the Max-Min CRI method suffers from drawbacks including: error-prone weighting strategy, inefficient compositional rule of inference, and subjective formulation of membership functions. Because of these prob...

Ontology is playing an increasingly important role in knowledge management and the Semantic Web. This study presents a novel episode-based ontology construction mechanism to extract domain ontology from unstructured text documents. Additionally, fuzzy numbers for conceptual similarity computing are presented for concept clustering and taxonomic relation definitions. Moreover, concept attributes...

as a generalization of the triple i method, the universal triple imethod is investigated from the viewpoints of both fuzzy reasoningand fuzzy controller. the universal triple i principle is putforward, which improves the previous triple i principle. then,unified form of universal triple i method is established based onthe (0,1)-implication or r-implication. moreover, the reversibilityproperty o...

rating medicinal plants based on the total number of drug shows that the mint plant species, withgeneral name mentha, among the most consumption herbs that are used in various industries such aspharmaceutical, food, cosmetics and health. drying process, in order to maintain the quality andquantity of essential oil extraction have a great role in the processing medicinal plants. importantaspects...

New methods, like fuzzy logic, are coming into the field of adaptive traffic signal control. Development of the fuzzy control can roughly be divided into two research approaches: development of fuzzy control functions, and development of fuzzy inference methods. Both approaches are discussed in this paper. First, a lately developed fuzzy inference method, called maximal fuzzy similarity, is int...

In this paper, a fuzzy Petri net approach to modeling fuzzy rule-based reasoning is proposed to bring together the possibilistic entailment and the fuzzy reasoning to handle uncertain and imprecise information. The three key components in our fuzzy rule-based reasoning-fuzzy propositions, truth-qualified fuzzy rules, and truth-qualified fuzzy facts-can be formulated as fuzzy places, uncertain t...

This paper addresses the problem of rate control for Available Bit Rate (ABR) service class in Asynchronous Transfer Mode (ATM) networks. An adaptive neurofuzzy mechanism based on Adaptive Network Fuzzy Inference System (ANFIS) for allocating rates in ABR service has been proposed and compared with the fuzzy technique called as Fuzzy Explicit Rate Marking (FERM). To achieve this, a neurofuzzy A...

This paper presents a hybrid model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning abil i ty of neural network with the inference mechanism of fuzzy logic . The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis . Significantly, the model can also construct a rel iable c...