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JLBuageuiei s.yHtera Level 2 inJcL-iiiaUoi proteasing and supervisory system Level 3 uMormation processing a.rioina-.ion Syy.e-* Figure13.1 Building Energy Management System with Fuzzy Control. historical and dynamic data processing, presentation, and analysis ensuring the well being of the occupants in order to improve productivity ensuring ancillary production and research-oriented climate conditions reducing energy consumption by optimal operation of the system. To...

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Ditches, cliffs and otherwise unstable surfaces. As in the Mars Pathfinder mission scenario, the navigation task can be facilitated by knowledge of a series of waypoints (path sub goals) furnished by mission operations personnel or an automated path planner, which lead to designated intermediate goals. Waypoints can be selected with the aid of images taken at the scene local to the rover. This mode of operation may also prevail on the 2003 rover mission, albeit with significantly longer...

262 Input Output Mapping

The input output mapping of a network is established according to the weights and the activation functions of their neurons in input, hidden and output layers. The number of input neurons corresponds to the number of input variables in the neural network, and the number of output neurons is the same as the number of desired output variables. The number of neurons in the hidden layer(s) depends upon the particular NN application. For example, consider the following two-layer feed-forward network...

Applications Of Neural Networks In Medicine And Biological Sciences

In this chapter, we will discuss applications of artificial neural networks (ANNs) in medicine and biological sciences. In particular, we will discuss ANN solutions to classical engineering problems of detection, estimation, extrapolation, interpolation, control, and pattern recognition as it pertains to these sciences. We will discuss some of these applications in detail to introduce the readers to typical problems that researchers face in the area. Research in ANNs' applications as an...

141 Introduction

During the past three decades, fuzzy logic has been an area of heated debate and much controversy. Zadeh, who is considered the founding father of the field, wrote the first paper in fuzzy set theory 1 , which is now considered to be the seminal paper of the subject. In that work, Zadeh was implicitly advancing the concept of human approximate reasoning to make effective decisions on the basis of available imprecise linguistic information 1 - 3 . The first implementation of Zadeh's idea was...

13 Fuzzy Logic Control

The fuzzy logic has been an area of heated debate and much controversy during the last three decades. The first paper in fuzzy set theory, which is now considered to be the seminal paper on the subject, was written by Zadeh 61 , who is considered the founding father of the field. In that work, Zadeh was implicitly advancing the concept of human approximate reasoning to make effective decisions on the basis of available imprecise linguistic information 62 , 63 . The first implementation of...

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4.3.3 Decision-making in Medical Treatment Strategies Decision-making techniques can be used in medicine to solve various problems. Specifically, ANN pattern recognition engines have enjoyed significant success in medical decision-making. 1 - 20 Although, the ANN systems developed in this area demonstrate great potential benefit to the healthcare community, due to the numerous remaining challenges, the area remains one of the most active. To introduce the difficulties that researchers face in...

155 Fuzzy Logic Control

RO desalination is a nonlinear process, which has to operate under specific conditions that are of utmost importance for plant operation optimization. The nonlinearity relates to changing process characteristics such as feed total dissolved solids and pH, which in turn cause changes to product quality and quantity parameters such as salt rejection and recovery. An RO desalination system is usually designed based on a defined set of data analysis such as flow, temperature, and feed water...

135 Application Of Fuzzy Control For Energy Management Of A Cascade Heating Center

Generation and consumptio n of heat power for domestic demand shou ld consider economical and ecological aspects. Optimal demand - oriented heat power generation by a cascade heat center requires sustainable evaluation of measurement information of the whole system. Fuzzy logic provides, by evaluation of the thermal behavior of the heating system, a powerful rule base for decision making in order to guarantee optimal operation of the heating system. Analysis of the dynamically thermal behavior...

Application Of Fuzzy Logic For Control Of Heating Chilling And Air Conditioning Systems

13.2 Building Energy Management System BEMS 13.3 Air Conditioning System FLC vs. DDC 13.3.4 Fuzzy Cascade Controller 13.4 Fuzzy Control for the Operation Management of a Complex Chilling System 13.4.2 Process Operation with FLC 13.4.3 Description of the Different Fuzzy Controllers 13.4.4 System Performance and Optimization with FLC 13.5 Application of Fuzzy Control for Energy Management of a Cascade Heating Center 13.5.2 FLC for System Optimization 13.5.4 Temperature Control Fuzzy vs. Digital

221 Model of Biological Neurons

In general, the human nervous system is a very complex neural network. The brain is the central element of the human nervous system, consisting of near 1010 biological neurons that are connected to each other through sub-networks. Each neuron in the brain is composed of a body, one axon and multitude of dendrites. The neuron model shown in Figure 2.1 serves as the basis for the artificial neuron. The dendrites receive signals from other neurons. The axon can be considered as a long tube, which...