Nowadays intelligent tools such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable methods for modeling an engineering system. This paper presents a new hybrid technique based on the combination of fuzzy inference system and artificial neural network for addressing navigational proble...

river flow forecasting for a region has a special and important role for optimal allocation of water resources. in this research, for forecasting river flow process, fuzzy inference system (fis) is used. three parameters including precipitation, temperature and daily discharge are used for forecasting of daily river flow of lighvan river located in lighvanchai watershed. for the initial preproc...

Building a Fuzzy Inference System (FIS) generally requires experts’ knowledge. However, experts’ knowledge is not always available. When there is few experts’ knowledge, it becomes hard to build a FIS using one of supervised learning methods. Meanwhile, Q-learning is a kind of reinforcement learning where an agent can acquire knowledge from its experiences even without the model of the environm...

Quality of Service (QoS) support in Mobile Ad hoc NETworks (MANETs) is a challenging task due to bandwidth and delay constraints, varying channel conditions, power limitations, node mobility and dynamic topology. This paper proposes an intelligent agent based ondemand (source initiated) delay aware QoS routing scheme in MANETs by using software agents that employ neuro-fuzzy logic supported by ...

A real-time operating system (RTOs) is often used in embedded system, to structure the application code and to ensure that the deadlines are met by reacting on events by executing the functions within precise time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical metrics. RTOs are generally implemented in software, increases computational overh...

The big hospitals’ electricity supply system’s reliability is discussed in this article through Petri nets and Fuzzy Inference System (FIS). To simulate analyse an electric power system, the FIS Mamdani MATLAB implemented. advantage of that it uses human experience to provide a faster solution than conventional techniques. elements involved are Main Electrical Power, Generator sets, Automatic T...

Lung cancer is distinguished by presenting one of the highest incidences and one of the highest rates of mortality among all other types of cancers. Detecting and curing the disease in the early stages provides the patients with a high chance of survival. This work aims at detecting lung nodules automatically through computerized tomography (CT) image. Accordingly, this article aim at presentin...

Despite the popularity and practical importance of fuzzy inference system (FIS), use an FIS model as n -ary aggregation function, which is characterized by both monotonicity boundary properties, yet to be established. This because research on ensuring that models satisfy property, i.e., monoton...

In this paper, the zero-order Sugeno Fuzzy Inference System (FIS) that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition (at the rule antecedent part) and...

In the past few years, an evolution in wireless communication has been emerged, along with a new type large potential application of network appears, which is Mobile Ad-Hoc Network (MANET). Black hole attack consider one most affected kind on MANET. Therefore, use intrusion detection system (IDS) major importance MANET protection. this paper, optimization fuzzy based proposed automate process p...