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: In this article, Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India.
Abstract: Optimal use of scarce water resources is the prime objective for water resources development projects in the developing country like India. Optimal releases have been generally expressed as a function of reservoir state variables and hydrologic inputs by a relationship which ultimately allows the policy/water managers to determine the water to be released as a function of available information. Optimal releases were obtained by using optimal control theory with inflow series and revised reservoir characteristics such as elevation area capacity table, zero elevation level as input in this study. Operating rules for reservoir were developed as a function of demand, water level and inflow. Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India. It was found that fuzzy logic model performed well compared to other soft computing techniques such as ANN, M5P and REPTree investigated in this study.
69 citations
TL;DR: The experimental results with the recognition problem of totally unconstrained handwritten numerals show that the genetic algorithm produces better results than the conventional methods such as averaging and Borda count.
69 citations
TL;DR: This papers highlights the previous researches and methods that has been used in the surface reconstruction field and chooses suitable methods based on the data used.
Abstract: Surface reconstruction means that retrieve the data by scanning an object using a device such as laser scanner and construct it using the computer to gain back the soft copy of data on that particular object It is a reverse process and is very useful especially when that particular object original data is missing without doing any backup Hence, by doing so, the data can be recollected and can be stored for future purposes The type of data can be in the form of structure or unstructured points The accuracy of the reconstructed result should be concerned because if the result is incorrect, hence it will not exactly same like the original shape of the object Therefore, suitable methods should be chosen based on the data used Soft computing methods also have been used in the reconstruction field This papers highlights the previous researches and methods that has been used in the surface reconstruction field
69 citations
Book•
30 Aug 2007
TL;DR: Rough Computing: Theories, Technologies and Applications offers the most comprehensive coverage of key rough computing research, surveying a full range of topics from granular computing to pansystems theory.
Abstract: Rough set theory is a new soft computing tool which deals with vagueness and uncertainty It has attracted the attention of researchers and practitioners worldwide, and has been successfully applied to many fields such as knowledge discovery, decision support, pattern recognition, and machine learning Rough Computing: Theories, Technologies and Applications offers the most comprehensive coverage of key rough computing research, surveying a full range of topics from granular computing to pansystems theory With its unique coverage of the defining issues of the field, this commanding research collection provides libraries with a single, authoritative reference to this highly advanced technological topic
69 citations
TL;DR: In this paper, the authors summarized working principle of various soft computing-based maximum power point tracking (MPPT) algorithms and compared each other based on the certain parameters like accuracy, tracking efficiency, SPV array dependency, convergence time, complexity of algorithm, hardware implementation, ability to handle partial shading conditions and variables used.
69 citations