Tag Archives: Fuzzy Logic

Application of Expert System for Diagnosing Medical Conditions: A Methodological Review (Published)

Naturally, human diseases should be treated on time; otherwise the patients might die if there is delay in attending to such patient or scarcity of medical practitioners’ or experts. Several attempts have been made through studies to design and built software based medical expert systems for probing and prognosis of several medical conditions using artificial and non-artificial based approaches for patients and medical facilities. This paper represents a comprehensive methodological review of existing medical expert systems used for diagnosis of various diseases based on the increasing demand of expert systems to support the human experts. The study provides a concise evaluation of the various techniques used such as rule-based, fuzzy, artificial neural networks and intelligent hybrid models. The rule-based techniques is not too efficient based on its inability  to learn and require powerful search strategies for its knowledge-base; while the fuzzy or ANN models are less efficient when compared to the hybrid models that can give a more accurate results.

Keywords: AI, ANN, Expert System, Fuzzy Logic, Intelligent hybrid model, Rule-based

Fuzzy Logic Based Quality of Service Evaluation in Multimedia Transmission over Ad Hoc Wireless Network (Published)

The use of ICT to bridge the gap that exists in the area of customer service satisfaction between an internet service provider (ISP) and the subscribing customer in the process of providing internet services cannot be overemphasized. Fuzzy logic has emerged as a tool to deal with qualitative decision making problems in order to achieve robustness, tractability, and low cost.  This paper proposes a fuzzy logic model for evaluation of quality of service (QoS) in multimedia transmission. In order to achieve our objectives, we develop a prototype of a computer aided system for an intelligent quality of service using fuzzy logic model.  The study designs a decision support system for the quality of service intelligence system. We design a fuzzy logic evaluator for the quality of service computing system using; MATLAB toolbox and windows 7 operating system. The result indicates that our model is able to detect and restore any QoS deterioration in real-time and thus, providing good and efficient QoS for customer satisfaction.

Keywords: Broadband Access System, Fuzzy Logic, Multimedia Transmission, Quality of Service (QoS)

AI Based Congestion Relief Method in GSM 900MHZ (Review Completed - Accepted)

It is commonly accepted that the problem of network congestion control remains a critical issue and a high priority, especially given the growing size, demand, and speed of the increasingly integrated services networks. This is where the need for an intelligent multi criteria handoff algorithm becomes apparent. Efficient load balancing algorithm is important in serving more mobile stations in the wireless networks.

This paper presents the design and implementation of a fuzzy multi-criteria handoff algorithm based on signal strength, path-loss and traffic load of base stations and the received signal to interference ratio as to balance traffic in all the neighboring sites at any time. This can be achieved by using Fuzzy Logic.

The proposed algorithm is able to balance load of the base station by handing off some ongoing calls on cell edge in highly loaded cells to migrate to overlapping under-loaded cells, such that the coverage area of loaded BTS virtually shrunk towards cell center of a loaded sector. In case of low load scenarios, the coverage area of a BTS is presumed to be virtually widened to cover up to the partial serving area of neighboring BTS. This helps a highly loaded neighboring BTS.

Keywords: Congestion, Fuzzy Logic, Handoff, Interference, Path loss, Received Signal Strength


The fetal electrocardiogram (FECG) signal is outcome of  the electrical activity of the fetal heart after 21 days of the pregnancy.  It contains  information  about the health  status of the fetus and so, an early diagnosis of any cardiac defects before delivery (Specially in case of  labour pain) increases the  chance of the appropriate treatment. In this paper we consider one signal from the thoracic and another from abdomen of the mother. The artificial neural network fuzzy inference system (ANFIS) is used to obtain the FECG component from abdominal ECG recording and reference thoracic maternal electrocardiogram (MECG) signal. The obtained FECG is being enhanced by using wavelet transform.

Keywords: ECG, FECG, Fuzzy Logic, MECG, Membership function and Wavelet transform, Neural network

A Comparative Analysis of Multi-Criteria Road Network (Published)

Travel Optimization is a method to find the best route to be followed for a journey between two points. This optimization can be based on factors one considers important while traveling. The work presented deals with the design of a multi-criteria based traffic network evaluation technique, using a variety of methods to calculate the cost of the feasible set of solutions, and then to decide which path is most desirable for a given requirement domain. Subsequently, various forms of the desired results e.g. the global depths of all the nodes in a given road network are extracted and presented; and compared by implementing the different methods of cost calculation: a weight based method and a Fuzzy Logic based mechanism. Both methods used are explained and compared through a case study to show that the aims are met in a useful way. Also among the aims of this research is to work out some way of solving the multi objective optimization problem of finding the shortest path using some optimization methods for given multiple objectives. The phenomenon of multiple criterions tells about the nature of the problem where increasing one or more objectives reduce effect of the rest of the criteria or criterions, which effectively, makes the solution more complex but comes out with better results and provides more knowledge of the problem itself.

Keywords: Fuzzy Logic, Multi-Criteria Optimization, Pareto Optimization, Road Network Analysis, Travel Optimization

Metric Genetic-Fuzzy Based Customer Relationship Management Health Model (Published)

Customer Relationship Management (CRM) is a model for managing a company’s interactions with current and future customers. Most of the implemented CRM approaches are subjective in nature, in addition to the serious need to separate feelings of satisfaction or dissatisfaction with the services delivery. Metric Genetic-Fuzzy Based Customer Relationship Management Health Model (MGFBCRMHM) was initiated for these reasons. Unified Modeling Language was utilized for modeling the software system, depicting clearly the interaction between various components and the dynamic aspect of the system. The simulation results utilizing Matrix Laboratory (MATLAB) was satisfactory. This paper demonstrates the practical application of metric based soft computing techniques in the health sector in determining patient’s satisfaction.

Keywords: CRM, Fuzzy Logic, Genetic Algorithm