The thesis focuses on risk assessment of selection of chosen company suppliers. It evaluates the quality of suppliers using principles of fuzzy logic and the determining rules. The evaluation of suppliers is conducted using programs MS Office Excel and MATLAB. The thesis contains a comparison of results of these two programs.

This thesis is analyzing customers of Geocart CZ a.s. company. Thesis is presenting new models of evaluating of customers. Weight mathematic model is created in MS Excel software. In software fuzzyTECH and MATLAB are designed fuzzy models for evaluating of customers with application of fuzzy logic. This method of evaluating should eliminate risk of mistakes with choosing of customers and minimize opportunity costs.

This Master's thesis deals with using the theory of fuzzy logic in building up a model of suppliers evaluation of Heidelberg Slovakia company. Using the model the company will obtain an image about the efficiency and reliability of its suppliers. The information can be used to decision making support in supply chain management.

The availability of water can be considered as one of the key ingredients to the human life, yet this resource remains scarcely available to those living in the rural parts of Africa. When water does present itself, it is often impure and requires extensive treatment. Water treatment systems, particularly those capable of treating water in rural areas, are currently areas of research and entrepreneurship focus, making a number of potential solutions available, and other still coming in. Unfortunately, these systems are not always capable of performing in particular socio-cultural and economic contexts, or are often deployed in the wrong rural areas. Therefore these systems do not perform at their optimal level of design. Rural areas in Africa have different socio-cultural and economic context from each other, and this needs to be taken into account if one is going to select the right water treatment system for a particular area. Using industrial engineering tools, two water treatment system selection models; an Additive Analytic Hierarchy Process model and a Fuzzy Logic based model, are presented and then integrated. These models take into account the context of selected rural area by pitting available water purification systems against selected criteria to determine if it is the right fit for the rural area considered. Both models are then pitted against each other to determine which is more adept at selecting the appropriate water purification system. Three water treatment alternatives were considered after an analysis was conducted on the available solutions on the market. The water treatment systems under consideration were the Biosand Filter with Zeolites (BSFZ), the Silver Impregnated Porous Pot, and A Borehole system. Makwane, a rural village in Limpopo, South Africa was used as a case study to demonstrate the application of the selection models. The BSFZ was selected as the ideal water treatment system to be implemented in Makwane / Dissertation (MEng)--University of Pretoria, 2016. / Industrial and Systems Engineering / MEng / Unrestricted

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This thesis investigates the application of Knowledge Based systems and Fuzzy Logic to automatic control. The knowledge used by a human operator is put in a computer usable form and applied to a control problem. The idea is not to attempt to enhance the stability or response of the system but given a basically stable and controllable system we apply human type control methods via a computer controller. A system can never be modelled exactly and therefore a controller design must allow for the uncertainty in the model. With fuzzy logic, the system inputs, outputs, parameters, reactions and cross coupling are represented in fuzzy or inexact variables, knowledge and reasoning. An exact (or nearly exact) model of the system is not necessary. A simple aircraft is the process to which this control method is applied. Knowledge, reasoning and feedback similar to what a human pilot utilizes are applied in the control of the process. / Thesis / Master of Engineering (ME)

When non-recurrent road traffic congestion happens, the operator of the traffic control centre has to select the most appropriate traffic control measure or combination of measures in a short time to manage the traffic network. This is a complex task, which requires expert knowledge, much experience and fast reaction. There are a large number of factors related to a traffic state as well as a large number of possible control measures that need to be considered during the decision making process. The identification of suitable control measures for a given non-recurrent traffic congestion can be tough even for experienced operators. Therefore, simulation models are used in many cases. However, simulating different traffic scenarios for a number of control measures in a complicated situation is very time-consuming. In this paper we propose an intelligent traffic control decision support system (ITC-DSS) to assist the human operator of the traffic control centre to manage online the current traffic state. The proposed system combines three soft-computing approaches, namely fuzzy logic, neural network, and genetic algorithm. These approaches form a fuzzy-neural network tool with self-organization algorithm for initializing the membership functions, a GA algorithm for identifying fuzzy rules, and the back-propagation neural network algorithm for fine tuning the system parameters. The proposed system has been tested for a case-study of a small section of the ring-road around Riyadh city. The results obtained for the case study are promising and show that the proposed approach can provide an effective support for online traffic control.

Yes / The next generation in mobility management will enable different mobile networks to interoperate with each other to ensure terminal and personal mobility and global portability of network services. However, in order to ensure global mobility, the deployment and integration of both satellite and terrestrial components are necessary. This article is focused on issues reltaed to mobility management in a future mobile communications system, in a scenario where a multisegment access network is integrated into an IP core network by exploiting the principles of Mobile IP. In particular, attention is given to the requirements for location, address, and handover management. In a heterogeneous environment, the need to perform handover between access networks imposes particular constraints on the type of information available to the terminal and network. In this case, consideration will need to be given to parameters other than radio characteristics, such as achievable quality of service and user preference. this article proposes a new approach to handover management by applying the fuzzy logic concept to a heterogeneous environment. The article concludes with the presentation of mobility management signaling protocols.

No / This paper presents an investigation of the design optimization in microstrip lines to reduce the crosstalk level using Fuzzy Logic. In microstrip lines length and spacing, termination conditions of interconnection and output impedance of gates are the major components that cause crosstalk. In order to design high speed printed circuit board (PCB) with optimum interconnection configuration, it is essential to reduce the crosstalk to its minimum tolerance level. A design methodology is proposed to correlate electrical parameters and physical configuration of lines to the crosstalk phenomena. This design is subsequently optimized using Fuzzy Logic to reduce the level of crosstalk. A set of experiments is carried out to demonstrate the capabilities of the design and optimization methods. The effect of the geometrical configuration of the lines on crosstalk, particularly the spacing, is highlighted.