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Linguistic Rules (linguistic + rule)
Selected AbstractsRule reduction in fuzzy logic for better interpretability in reservoir operationHYDROLOGICAL PROCESSES, Issue 21 2007C. Sivapragasam Abstract Decision-making in reservoir operation has become easy and understandable with the use of fuzzy logic models, which represent the knowledge in terms of interpretable linguistic rules. However, the improvement in interpretability with increase in number of fuzzy sets (,low', ,high', etc) comes with the disadvantage of increase in number of rules that are difficult to comprehend by decision makers. In this study, a clustering-based novel approach is suggested to provide the operators with a limited number of most meaningful operating rules. A single triangular fuzzy set is adopted for different variables in each cluster, which are fine-tuned with genetic algorithm (GA) to meet the desired objective. The results are compared with the multi fuzzy set fuzzy logic model through a case study in the Pilavakkal reservoir system in Tamilnadu State, India. The results obtained are highly encouraging with a smaller set of rules representing the actual fuzzy logic system. Copyright © 2007 John Wiley & Sons, Ltd. [source] Learning weighted linguistic rules to control an autonomous robotINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 3 2009M. Mucientes A methodology for learning behaviors in mobile robotics has been developed. It consists of a technique to automatically generate input,output data plus a genetic fuzzy system that obtains cooperative weighted rules. The advantages of our methodology over other approaches are that the designer has to choose the values of only a few parameters, the obtained controllers are general (the quality of the controller does not depend on the environment), and the learning process takes place in simulation, but the controllers work also on the real robot with good performance. The methodology has been used to learn the wall-following behavior, and the obtained controller has been tested using a Nomad 200 robot in both simulated and real environments. © 2009 Wiley Periodicals, Inc. [source] Storage of linguistic information in a continuous classifying associative memoryINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 6 2002Antonio B. Bailón In this article, we analyze the use of the continuous classifying associative memory (CCLAM) to store linguistic information. Freedom in the choice of the functions that control the operation of the CCLAM equip this memory with the capacity to adapt to different information storage and recovery needs. We begin with the problem of storing linguistic terms by memorizing the patterns formed by the degrees of compatibility with these terms. After that, the problem of storing linguistic rules is discussed. Let us remark that in these cases not a single CCLAM is used, but rather a set of them connected in suitable structured ways. © 2002 Wiley Periodicals, Inc. [source] New Traversability Indices and Traversability Grid for Integrated Sensor/Map-Based NavigationJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2003Homayoun Seraji This paper presents new measures of terrain traversability at short range and long range of a mobile robot; namely, local and global traversability indices. The sensor-based local traversability index is related by a set of linguistic rules to large obstacles and surface softness within a short range of the robot measured by on-board sensors. The map-based global traversability index is obtained from the terrain topographic map, and is based on major surface features such as hills and lakes within a long range of the robot. These traversability indices complement the mid-range sensor-based regional traversability index introduced earlier. Each traversability index is represented by four fuzzy sets with the linguistic labels {POOR, LOW, MODERATE, HIGH}, corresponding to surfaces that are unsafe, moderately-unsafe, moderately-safe, and safe for traversal, respectively. The global terrain analysis also leads to the new concepts of traversability map and traversability grid for representation of terrain quality based on the global map information. The traversability indices are used in two sensor-based traverse-local and traverse-regional behaviors and one map-based traverse-global behavior. These behaviors are integrated with a map-based seek-goal behavior to ensure that the mobile robot reaches its goal safely while avoiding both sensed and mapped terrain hazards. This provides a unified system in which the two independent sources of terrain quality information, i.e., prior maps and on-board sensors, are integrated together for reactive robot navigation. The paper is concluded by a graphical simulation study. © 2003 Wiley Periodicals, Inc. [source] | ||||||||||