Topic
Soft computing
About: Soft computing is a research topic. Over the lifetime, 6710 publications have been published within this topic receiving 118508 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: The paper proposes a framework for the development of soft computing-based controllers in modern greenhouses by applying artificial intelligence (AI) techniques to the modeling and control of some climate variables within a greenhouse.
Abstract: The methodology proposed in the paper applies artificial intelligence (AI) techniques to the modeling and control of some climate variables within a greenhouse. The nonlinear physical phenomena governing the dynamics of temperature and humidity in such systems are, in fact, difficult to model and control using traditional techniques. The paper proposes a framework for the development of soft computing-based controllers in modern greenhouses.
104 citations
TL;DR: A state-of-charge (SOC) estimation system for the lead-acid battery, which is free from the time-dependent variation of the battery characteristics, is developed by using an improved Coulomb metric method and the learning system uses the fuzzy logic.
103 citations
01 Jan 2003
TL;DR: The fact that size-optimal solutions for implementing arbitrary Boolean functions using threshold gates have sub-linear fan-ins is encouraging, as the area and the delay of VLSI implementations are related to the fan-in of the gates.
Abstract: This paper discusses size-optimal solutions for implementing arbitrary Boolean functions using threshold gates. After presenting the state-of-the-art, we start from the result of Horne and Hush [12], which shows that threshold gate circuits restricted to fan-in 2 can implement arbitrary Boolean functions, but require O(2/n) gates in 2n layers. This result will be generalized to arbitrary fan-ins (∆), lowering the depth to n/log∆ + n/∆, and proving that all the (relative) minimums of size are obtained for sub-linear fan-ins (∆ < n − logn). The fact that size-optimal solutions have sub-linear fan-ins is encouraging, as the area and the delay of VLSI implementations are related to the fan-in of the gates.
103 citations
TL;DR: Experiments demonstrate that although soft computing methods are somewhat of tolerant of inaccurate inputs, cleaned data results in more robust models for practical problems, due to its simplicity in parameter selection and its fitness in the target problem.
103 citations
TL;DR: The effectiveness of the proposed fuzzy modeling method is shown and compared with two other soft computing techniques: multi-layer perceptron neural networks and case-based reasoning and the comparative results indicate that the proposed method is consistently superior to the other two methods.
Abstract: This paper presents a fuzzy modeling method proposed by Wang and Mendel for generation of fuzzy rules using data generated from a simulated model that is built from a real factory located in Hsin-Chu science-based park of Taiwan, R.O.C. The fuzzy modeling method is further evolved by a genetic algorithm for due-date assignment problem in manufacturing. By using simulated data, the effectiveness of the proposed method is shown and compared with two other soft computing techniques: multi-layer perceptron neural networks and case-based reasoning. The comparative results indicate that the proposed method is consistently superior to the other two methods.
103 citations