The selection of a tourism development site involves a complex array of decision criteria that may have interdependence relationships within and between them. In the process of finding the optimum location that meet desired conditions, the analyst is challenged by the tedious manipulation of spatial data and the management of multiple decision-making criteria. This paper presents a novel decision making framework in which expert systems (ES), and geographic information systems–based multicriteria evaluation techniques (Analytical Network Process and fuzzy quantifiers-guided ordered weighted averaging operators (GIS-based ANP-OWA)) are integrated systematically to facilitate the selection of suitable sites for building new tourism facilities. First, ES is used for recommending the proper site selection criteria and their interdependence relationships. Then, the GIS-based ANP-OWA is used to perform the spatial data analysis necessary to generate a wide range of possible candidate sites’ scenarios taking into accounts both the interdependence relationships between sitting criteria and the level of risk the decision-makers wish to assume in their multicriteria evaluation. A typical case study is presented to demonstrate the application of the proposed decision making framework.

This paper proposes a hybrid approach based on limit-cycles method and fuzzy logic controller for the problem of obstacle avoidance of mobile robots in unknown environment. The purpose of hybridization consists on the improvement of basic limit-cycle method in order to obtain safe and flexible navigation. The proposed algorithm has been successfully tested in different configurations on simulation.

Based on the equal-cycle nested graph, the power-cycle nested graph is brought forward. In this paper, we research on the largest edge-balance index of the graph C_(7^m)×P_(m_7) (m≡2(mod3))(m≥5) by the methods and techniques of graph theory and combinatorial mathematics, and solve formula proof and graphic tectonic methods.

In this paper, a fuzzy logic control (FLC) is proposed for maximum power point tracking (MPPT) in wind turbine connection to Permanent Magnet Synchronous Generator (PMSG). The proposed fuzzy logic controller tracks the maximum power point (MPP) by measurements the load voltage and current. This controller calculates the load power and sent through the fuzzy logic system. The main goal of this paper is design of the fuzzy logic controller in the model of DC-DC converter (boost converter). This method allows the MPPT controller output (duty cycle) adjusts the voltage input to the converter to track the maximum power point of the wind generator.

This paper presents an improved artificial bee colony (IABC) optimization method to solving practical economic dispatch taking into account the nonlinear generator characteristics such as valve-point loading effects. In order to exploit the performance of this new variant based ABC method to solving practical economic dispatch, a new local search mechanism (LSM) associated to the original ABC algorithm; it allows exploiting effectively the promising region to locate the best solution. The proposed approach has been examined and applied to many practical electrical power systems, the 13 generating units, and to the large electrical system with 40 generating units considering valve point loading effects. From the different case studies, it is observed that the results compared with the other recent techniques demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical and large ED.

Inverted Pendulum is a well established benchmark problem that produces many challenges to a control engineer. It is a nonlinear, unstable, non minimumphase and under actuated system.Itrequires a controller which canadapt in different disturbance conditions and work appreciably well when compared to conventional controllers. In this paper Interval type-2 Fuzzy logic controllerfor inverted pendulum isdesigned.The objective of the proposed control technique is to develop the stability position of the pendulum. The optimal membership functions and the interference system are developed using IT2FLS. Using the IT2FLS, the position of the inverted pendulum is maintained towards the reference position. The proposed control techniqueis implemented in MATLAB/Simulink working platform and the control performances are evaluated. Then, the performance of proposed controller is evaluated and compared with the PI controller, Fuzzy controller andABC- FLC.

Presence of distributed generation (DG) in distribution systems has significant impacts on the operational characteristics of these systems, also using capacitor for reactive compensation and loss reduction is so common. Injected harmonic currents from non-linear loads into distribution system distort all of voltages and currents and must be considered when placing the capacitor banks so that the resonance will not occur. Distributed Generation is often connected to the network via power-electronic interfaces for a proper coupling with the distribution networks. Inverters are capable of producing harmonic components and can be used as ancillary services for reducing harmonics by designing of a proper controlling system. In this paper discrete particle swarm optimization (DPSO) approach is used for the optimal placement and sizing of distributed generations and capacitors in distorted distribution systems for simultaneous voltage profile improvement, loss and total harmonic distortion (THD) reduction. Constraints include voltage limit, voltage THD, number/ size of capacitors and generators. For evaluating the proposed algorithm, the IEEE 33-bus test system is modified and employed.

Information security management is a part of information management, whose main task is to determine information goals and remove obstacles on the way of achieving such goals with providing necessary strategies. Information management is responsible to implement and control the performance of the organization`s security system while tries to keep it up to date. The purpose of information security management in an organization is maintaining different sorts of resources as software, hardware, information, communication and human resources.
The organization needs an integrated program against threats such as unauthorized access to information, environmental risks and dangers caused by users. In the present paper, the IT risk in an organization was assessed through an intelligent system benefiting from fuzzy analysis and certainty factors. As most of ambiguity samples have a level of belie, so doubt and the degree of membership were calculated as a part of output in the system and a better result achieved compared to previous methods.

Cooperative communication in wireless networks has become more and more attractive recently since it could mitigate the particularly severe channel impairments arising from multipath propagation. Here the greater benefits gained by exploiting spatial diversity in the channel. In this paper, an overview on cooperative communication in wireless networks is presented. We inscribe the benefits of cooperative transmission than traditional non – cooperative communication. Practical issues and challenges in cooperative communication are identified. In particular, we present a study on the advantages, applications and different routing strategies for cooperative mesh networks, Ad hoc networks and wireless sensor networks.

This research is focused on proposed minimum rule base PID computed torque algorithms with application to continuum robot manipulator. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. Classical Computed Torque Controller (CTC) is robust to control model partly uncertainties and external disturbances. This controller is one of the significant nonlinear methodologies; according to the nonlinear dynamic formulation. One of the main targets in this research is increase the robustness based on the artificial intelligence methodology. Classical computed torque control has difficulty in handling unstructured model uncertainties. One can overcome this problem by combining a computed torque controller and artificial intelligence (e.g. fuzzy logic). To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large number of fuzzy rules will cause a high computation load. To reduce the number of rule base this research is focused on the PD like fuzzy plus integral methodology. This method is applied to continuum robot manipulator to have the best performance.