An Adaptive Fuzzy-Based Service-Oriented Approach with QoS Support for Vehicular Ad Hoc Networks

An attempt in implementing on-demand, QoS supported Vehicular Ad hoc Network (VANET) routing algorithms has taken new dimensions. Delivering information in time to achieve reliability across vehicles (nodes) is still being a challenge among the VANET research groups. An effort to develop a QoS adaptive routing schemes using soft computing techniques is made in this research work. SADVA – An adaptive fuzzy based QoS service oriented approach for VANET is presented in this paper. The performance of SADVA is compared with AODV (Perkins, Royer, & Das, 2003), GV-GRID (Li, & Yu, 2007), DSR (Johnson, Maltz, & Hu, 2004), FSR (Gerla, 2002), DYMO (Chakeres, & Perkins, 2006), REDEM (Prabhakar, Sivanandham, & Arunkumar, 2011b), and QARS (Prabhakar et al, 2011a). SADVA employs fuzzy logic system to determine the vehicle's speed over an effective time period for different types of service in use between multiple VANET nodes to engage or cooperate in communication. This chapter focuses on designing and developing QoS aware routing protocol for multi-hop VANET. Metrics such as number of packets received per second, percentage of packet loss and time for route establishment are used to analyse the network situation. Simulation test runs are carried out using Two Ray Ground propagation model where vehicular traffic is generated according to a Poisson process.

Solution of Basic Inventory Model in Fuzzy and Interval Environments

In this present paper a basic inventory model is solved in different imprecise environments. Four different cases are discussed: 1) Crisp inventory model, that is, the quantity at present and demand is crisp number; 2) Inventory model in fuzzy environment, that is, the quantity and demand both are fuzzy number; 3) Inventory model in interval environment, that is, the quantity and demand both are interval number and lastly; 4) Inventory model in time dependent fuzzy environment, that is, quantity and demand are both time dependent fuzzy number. Different numerical examples are used to illustrate the model as well as to compute the efficiency of imprecise differential equation approach to solve the model.

Optimized-Fuzzy-Logic-Based Bit Loading Algorithms

Next generation wireless communication systems promise the subscribers with Giga-bit-data-rate experience at low Bit Error Rate (BER) under adverse channel conditions. In order to maximize the overall system throughput of Orthogonal Frequency Division Multiplexing (OFDM), adaptive modulation is one of the key solutions. In adaptive modulated OFDM, the subcarriers are allocated with data bits and energy in accordance with the Signal to Interference Ratio (SIR) of the multipath channel, which is referred to as adaptive bit loading and adaptive power allocation respectively. The number of iterations required allocating the target bits and energy to a sub channel is optimized. The key choice of the paper is to allocate the bits with minimum number of iterations after clustering the sub channels using fuzzy logic. The proposed method exhibits a faster convergence in obtaining the optimal solution.

Fuzzy-Based Matrix Converter Drive for Induction Motor

In industrial applications, approximately, 60% of world's consumption of electrical energy passes through the windings of squirrel-cage induction motors. Hence it is necessary to select an efficient drive circuit for induction motor to save energy. The MC are preferred to replace VSC in industrial applications. To control the performance of the MC, fuzzy logic technique is proposed and simulated using Matlab/Simulink. In this chapter, the basic concepts of MCs are discussed. The implementation of fuzzy logic technique to improve the performance of MC in driving induction motor is discussed in detail. The design of fuzzy controllers and the closed loop control of induction motor is shown. It seen that the introduction of fuzzy controllers in the closed loop helped to reduce the overshoot at starting and maintain the reference speed when running with load torque. Also the input and output voltage of the MC is maintained sinusoidal.

The Fuzzy-AHP and Fuzzy TOPSIS Approaches to ERP Selection

The proposed chapter aims at explaining theoretical frameworks of the Fuzzy AHP and Fuzzy TOPSIS extension approaches and also summarizes the recent research around these two concepts. To help reader understand the practical usage of the two approaches, it also demonstrates their applications on the significant problem of ERP Selection. The techniques are further illustrated with the help of an organization case study located in NCR, Delhi (India). Further, a comparative analysis will be made between the two techniques by taking into account their time complexities.

Clustering Approaches in Decision Making Using Fuzzy and Rough Sets

Data clustering has been an integral and important part of data mining. It has wide applications in database anonymization, decision making, image processing and pattern recognition, medical diagnosis and geographical information systems, only to name a few. Data in real life scenario are having imprecision inherent in them. So, early crisp clustering techniques are very less efficient. Several imprecision based models have been proposed over the years like the fuzzy sets, rough sets, intuitionistic fuzzy sets and many of their generalized versions. Of late, it has been established that the hybrid models obtained as combination of these imprecise models are far more efficient than the individual ones. So, many clustering algorithms have been put forth using these hybrid models. The focus of this chapter is to discuss on some of the data clustering algorithms developed so far and their applications mainly in the area of decision making.

A Fuzzy-Based Calorie Burn Calculator for a Gamified Walking Activity Using Treadmill

Gamification can be viewed as a process design which encapsulates competition, achievements, status and self-expression. Gamification is used as a tool for improving physical fitness. In this chapter the physical activity using treadmill walking is considered. Calorie burn calculation plays a vital role in the gamification design. In treadmill calorie burn calculation, traditional and fuzzy based methods are compared for effective gamification. In the traditional calorie burn calculation method different equations are used for different incline levels. In the fuzzy logic method fuzzy reasoning technique is applied to calculate the calorie burn for different incline levels. It is identified that fuzzy based calorie calculation enhances physical activity and supports Gamification. Fuzzy based calorie burn calculation methods produces approximate values and supports the players to choose higher incline levels instead of lower incline levels and thereby burning more calories.

Outliers, Missing Values, and Reliability

Reliability is a major concern in qualitative research. Most of the current research deals with finding the reliability of the data, but not much work is reported on how to improve the reliability of the unreliable data. This paper discusses three important aspects of the data pre-processing: how to detect the outliers, dealing with the missing values and finally increasing the reliability of the dataset. Here authors have suggested a framework for pre-processing of the inter-judged data which is incomplete and also contains erroneous values. The suggested framework integrates three approaches, Krippendorff's alpha for reliability computation, frequency based outlier detection method and a hybrid fuzzy c-means and multilayer perceptron based imputation technique. The proposed integrated approach results in an increase of reliability for the dataset which can be used to make strong conclusions.

Bio-Inspired Computing through Artificial Neural Network

Developing suitable mathematical or algorithmic model to solve real life complex problems is one of the major challenges faced by the researchers especially those involved in the computer science field. To a large extent Computational intelligence has been found to be effective in designing such models. Bio inspired computing is the technique which makes the machines intelligent by adapting the behavior and methods exhibited by the human beings and other living organisms while forming intelligent systems. These intelligent models include the intelligent techniques such as Artificial Neural Network (ANN), evolutionary computation, swarm intelligence, fuzzy system, artificial immune system accompanied by fuzzy logic, expert system, deductive reasoning. All these together form the area of Bio inspired computing. The chapter deals with various bio inspired technique, giving emphasis on issues, development, advances and practical implementations of ANN.

Fuzzy Dynamic Programming Problem for Single Additive Constraint with Additively Separable Return by Means of Trapezoidal Membership Functions

Dynamic Programming Problem (DPP) is a multivariable optimization problem is decomposed into a series of stages, optimization being done at each stage with respect to one variable only. DP stands a suitable quantitative study procedure that can be used to explain various optimization problems. It deals through reasonably large as well as complex problems; in addition, it involves creating a sequence of interconnected decisions. The technique offers an efficient procedure for defining optimal arrangement of decisions. Throughout this chapter, solving procedure completely deliberate about as Fuzzy Dynamic Programming Problem for single additive constraint with additively separable return with the support of trapezoidal membership functions and its arithmetic operations. Solving procedure has been applied from the approach of Fuzzy Dynamic Programming Problem (FDPP). The fuzzified version of the problem has been stated with the support of a numerical example for both linear and nonlinear fuzzy optimal solutions and it is associated to showing that the proposed procedure offers an efficient tool for handling the dynamic programming problem instead of classical procedures. As a final point the optimal solution with in the form of fuzzy numbers and justified its solution with in the description of trapezoidal fuzzy membership functions.