The Impact of Soft Computing on Building Norms and Certification in Engineering

2011 ◽  
Author(s):  
M. Phiri
Keyword(s):  
Soft Computing ◽  
The Impact

scholarly journals Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Distributed Intelligence ◽  
High Level ◽  
The Impact ◽  
Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

The impact of soft computing for the progress of artificial intelligence

2011 ◽  
Vol 11 (2) ◽  
pp. 1491-1492 ◽  
Author(s):  
Oscar Cordón ◽  
Antonio Fernández-Caballero ◽  
José A. Gámez ◽  
Frank Hoffmann
Keyword(s):  
Artificial Intelligence ◽  
Soft Computing ◽  
The Impact

scholarly journals Using a Modified VIKOR Technique for Evaluating and Improving the National Healthcare System Quality

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1349
Author(s):  
Sun-Weng Huang ◽  
James J. H. Liou ◽  
Hai-Hua Chuang ◽  
Gwo-Hshiung Tzeng
Keyword(s):  
Decision Making ◽  
Healthcare System ◽  
Soft Computing ◽  
Evaluation Framework ◽  
System Quality ◽  
Health Security ◽  
Decision Making Processes ◽  
Vikor Technique ◽  
Criteria Importance ◽  
The Impact

The effectiveness of the national/regional healthcare system is one of the keys to prevent the spread of COVID-19. In the face of this unknown pandemic, where the healthcare system should continue to be promoted and improved are crucial decision issues. In the past, most studies have used the subjective opinions of experts for analysis and decision-making processes when investigating complicated decision-making problems. However, such decision-making processes are easily influenced by experts’ preferences. Therefore, this research proposes a soft computing technology that integrates CRiteria Importance Through Intercriteria Correlation (CRITIC) with the modified VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning multicriteria optimization and compromise solution (modified VIKOR) technique to reduce the impact of expert preference. In order to cope with the fact that COVID-19 has spread globally and to discover problems quickly and effectively, this study uses the global health security (GHS) index as the evaluation framework and conducts overall discussions in 195 countries/regions around the world. It is verified that the technology of soft computing can be used for continuous promotion and improvement of the national/regional healthcare system. This technology facilitates decision makers to know the gap of performance between the current healthcare system and the aspiration level. Finally, based on these gaps, we provide management advice to help improve these systems.

An Intelligent Location Prediction System for Wind Farms Using Belief Networks

2020 ◽  
Vol 17 (8) ◽  
pp. 3412-3415
Author(s):  
P. Sardar Maran ◽  
K. Ashokkumar ◽  
J. Refonaa ◽  
Jany Shabu ◽  
A. Jesudoss ◽  
...  
Keyword(s):  
Neural Network ◽  
Wind Energy ◽  
Soft Computing ◽  
Alternative Energy ◽  
Machine Language ◽  
Energy Output ◽  
Energy Sources ◽  
Soft Computing Techniques ◽  
Ecological Parameters ◽  
The Impact

An energy crisis is a major problem India is facing today. Alternative energy sources are very important today to overcome the impact of rising oil prices. The main alternative energy source is the power from wind energy sources having 10% in India’s total energy consumption. The wind farm location planning to achieve the best energy output generation is in need of a finding solution. In this article, together with the belief network, a challenge is made exactly to prospects the energy from wind resources with and applied a statistical approach. Soft Computing techniques play a major role in the research applications especially in the multi-disciplinary areas. According to the technological development various soft computing techniques can be used in many areas to analyze the problem including Artificial Neural Network, Fuzzy logic, Adaptive Neuro and machine language. In this study the potential location of wind energy is identified by the belief neural network technique. The basic concept of Bayesian uncertainty treatment is that this analysis analyzes the conditional probability of occurrence. In addition, a particular region’s ecological parameters and environmental issues are also important. The ecological parameters and environmental factors also involved in the wind velocity of a particular region.

scholarly journals Relations between the Complex Neutrosophic Sets with Their Applications in Decision Making

Axioms ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 64 ◽  
Author(s):  
Ashraf Al-Quran ◽  
Shawkat Alkhazaleh
Keyword(s):  
Student Performance ◽  
Soft Computing ◽  
Cartesian Product ◽  
Real Life ◽  
Time Frame ◽  
Real Space ◽  
Membership Functions ◽  
Neutrosophic Sets ◽  
Computing Technique ◽  
The Impact

The basic aim of soft computing is to trade precision for a tractableness and reduction in solution cost by pushing the limits of tolerance for imprecision and uncertainty. This paper introduces a novel soft computing technique called complex neutrosophic relation (CNR) to evaluate the degree of interaction between two complex neutrosophic sets (CNSs). CNSs are used to represent two-dimensional information that are imprecise, uncertain, incomplete and indeterminate. The Cartesian product of CNSs and subsequently the complex neutrosophic relation is formally defined. This relation is generalised from a conventional single valued neutrosophic relation (SVNR), based on CNSs, where the ranges of values of CNR are extended to the unit circle in complex plane for its membership functions instead of [0, 1] as in the conventional SVNR. A new algorithm is created using a comparison matrix of the SVNR after mapping the complex membership functions from complex space to the real space. This algorithm is then applied to scrutinise the impact of some teaching strategies on the student performance and the time frame(phase) of the interaction between these two variables. The notion of inverse, complement and composition of CNRs along with some related theorems and properties are introduced. The performance and utility of the composition concept in real-life situations is also demonstrated. Then, we define the concepts of projection and cylindric extension for CNRs along with illustrative examples. Some interesting properties are also obtained. Finally, a comparison between different existing relations and CNR to show the ascendancy of our proposed CNR is provided.

scholarly journals Analysis of Harassment Complaints to Detect Witness Intervention by Machine Learning and Soft Computing Techniques

2021 ◽  
Vol 11 (17) ◽  
pp. 8007
Author(s):  
Marina Alonso-Parra ◽  
Cristina Puente ◽  
Ana Laguna ◽  
Rafael Palacios
Keyword(s):  
Machine Learning ◽  
Soft Computing ◽  
Language Processing ◽  
Public Awareness ◽  
Free Text ◽  
Soft Computing Techniques ◽  
Awareness Raising ◽  
Processing Techniques ◽  
The Impact ◽  
The City

This research is aimed to analyze textual descriptions of harassment situations collected anonymously by the Hollaback! project. Hollaback! is an international movement created to end harassment in all of its forms. Its goal is to collect stories of harassment through the web and a free app all around the world to elevate victims’ individual voices to find a societal solution. Hollaback! pretends to analyze the impact of a bystander during a harassment in order to launch a public awareness-raising campaign to equip everyday people with tools to undo harassment. Thus, the analysis presented in this paper is a first step in Hollaback!’s purpose: the automatic detection of a witness intervention inferred from the victim’s own report. In a first step, natural language processing techniques were used to analyze the victim’s free-text descriptions. For this part, we used the whole dataset with all its countries and locations. In addition, classification models, based on machine learning and soft computing techniques, were developed in the second part of this study to classify the descriptions into those that have bystander presence and those that do not. For this machine learning part, we selected the city of Madrid as an example, in order to establish a criterion of the witness behavior procedure.

Formation of Lunar Craters and Bright Rays as a Result of Meteorite Impacts

1962 ◽  
Vol 14 ◽  
pp. 415-418
Author(s):  
K. P. Stanyukovich ◽  
V. A. Bronshten
Keyword(s):  
Explosive Charge ◽  
The Moon ◽  
Meteorite Impacts ◽  
The Earth ◽  
Lunar Craters ◽  
The Impact

The phenomena accompanying the impact of large meteorites on the surface of the Moon or of the Earth can be examined on the basis of the theory of explosive phenomena if we assume that, instead of an exploding meteorite moving inside the rock, we have an explosive charge (equivalent in energy), situated at a certain distance under the surface.

The Geosciences Applied to Lunar Exploration

1962 ◽  
Vol 14 ◽  
pp. 169-257 ◽  
Author(s):  
J. Green
Keyword(s):  
Lunar Surface ◽  
Probable Mechanism ◽  
Point Of View ◽  
Lunar Exploration ◽  
Geological Model ◽  
Apply Geophysics ◽  
Surface Features ◽  
The Impact

The term geo-sciences has been used here to include the disciplines geology, geophysics and geochemistry. However, in order to apply geophysics and geochemistry effectively one must begin with a geological model. Therefore, the science of geology should be used as the basis for lunar exploration. From an astronomical point of view, a lunar terrain heavily impacted with meteors appears the more reasonable; although from a geological standpoint, volcanism seems the more probable mechanism. A surface liberally marked with volcanic features has been advocated by such geologists as Bülow, Dana, Suess, von Wolff, Shaler, Spurr, and Kuno. In this paper, both the impact and volcanic hypotheses are considered in the application of the geo-sciences to manned lunar exploration. However, more emphasis is placed on the volcanic, or more correctly the defluidization, hypothesis to account for lunar surface features.

Asteroid and Comet Impact Speeds upon Mars: Significance for Panspermia and the Supply of Organics

1997 ◽  
Vol 161 ◽  
pp. 197-201 ◽  
Author(s):  
Duncan Steel
Keyword(s):  
Probability Distributions ◽  
Regions Of Interest ◽  
Significant Fraction ◽  
Organic Chemicals ◽  
Impact Speed ◽  
The Mean ◽  
The Impact

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.

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