Search results for "Soft computing"
showing 10 items of 45 documents
Surrogate models for the compressive strength mapping of cement mortar materials
2021
Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method available in the literature, which can reliably predict their strength based on the mix components. This limitation is attributed to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques for predicting the compressive strength of mortars is investigated. Specifically, Levenberg–Marquardt, biogeography-based optimization, and invasive weed optimization algorithms are used for this purpose (based on experimental data available in the literature). The c…
Exploring the use of multi-gene genetic programming in regional models for the simulation of monthly river runoff series
2023
The use of new data-driven approaches based on the so-called expert systems to simulate runoff generation processes is a promising frontier that may allow for overcoming some modeling difficulties related to more complex traditional approaches. The present study highlights the potential of expert systems in creating regional hydrological models, for which they can benefit from the availability of large database. Different soft computing models for the reconstruction of the monthly natural runoff in river basins are explored, focusing on a new class of heuristic models, which is the Multi-Gene Genetic Programming (MGGP). The region under study is Sicily (Italy), where a regression based rain…
A very brief history of soft computing: Fuzzy Sets, artificial Neural Networks and Evolutionary Computation
2013
This paper gives a brief presentation of history of Soft Computing considered as a mix of three scientific disciplines that arose in the mid of the 20th century: Fuzzy Sets and Systems, Neural Networks, and Evolutionary Computation. The paper shows the genesis and the historical development of the three disciplines and also their meeting in a coalition in the 1990s.
Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks
2019
The present paper discussed the development of a reliable and robust artificial neural network (ANN) capable of predicting the tribological performance of three highly alloyed tool steel grades. Experimental results were obtained by performing plane-contact sliding tests under non-lubrication conditions on a pin-on-disk tribometer. The specimens were tested both in untreated state with different hardening levels, and after surface treatment of nitrocarburizing. We concluded that wear maps via ANN modeling were a user-friendly approach for the presentation of wear-related information, since they easily permitted the determination of areas under steady-state wear that were appropriate for use…
Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring
2018
Abstract. New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sen…
Early Vision and Soft Computing
2002
The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. For example, it can be used to introduce flexibility in artificial systems and possibly to improve their Intelligent Quotient. Aim of this paper is to describe the applicability of soft-computing to early vision problems. The good performance of this approach is claimed by the fact that digital images are examples of fuzzy entities, where geometry of shapes are not always describable by exact equations and their approximation can be very complex.
FUZZINESS: the emergence of a new scientific concept
2011
Fuzzy Set Theory as a methodological bridge between hard science and humanities
2014
In this paper, we will investigate the possible role of fuzzy set theory (FST), and more generally the ensemble of technologies and theoretical approaches known as soft computing, as a method- ological bridge between hard sciences and humanities. We will try, building on previous works, to investigate the “family links” between these disciplines and show how FST may be of help in promoting a connection between the “two cultures”. We will discuss Carnap and his paradox of explication, the dilemma between imagination and rigor according to Bateson, the problem of interdisciplinarity, and the consequences of precision and exactness.
Soft Computing and Image Analysis
2000
The paper describes a soft approach to solve image analysis problems. Theory of fuzzy-sets has been used to implement most of the algorithms described in the paper. Soft approaches can be useful to extend mathematical morphology operators on gray level images and to describe the shape of dotted objects. Examples on real data are also provided.