Soft computing and statistical tools for developing analytical models

2021 ◽  
pp. 247-325
Author(s):  
Hoseyn Sayyaadi
Keyword(s):  
Soft Computing ◽  
Analytical Models ◽  
Statistical Tools

Evaluating the Applicability of Analytical Models for Silicone Tube Mckibben Actuators through Soft Computing

2021 ◽  
Author(s):  
Debadrata Sarkar ◽  
Shounak Dasgupta ◽  
Soumen Sen ◽  
Shibendu Shekhar Roy ◽  
Aman Arora
Keyword(s):  
Soft Computing ◽  
Analytical Models ◽  
Silicone Tube ◽  
Mckibben Actuators

scholarly journals Geomatics and Soft Computing Techniques for Infrastructural Monitoring

2020 ◽  
Vol 12 (4) ◽  
pp. 1606 ◽  
Author(s):  
Vincenzo Barrile ◽  
Antonino Fotia ◽  
Giovanni Leonardi ◽  
Raffaele Pucinotti
Keyword(s):  
Soft Computing ◽  
Structural Model ◽  
Control Unit ◽  
Machine Learning Techniques ◽  
Analytical Models ◽  
Risk Level ◽  
Behavior Monitoring ◽  
Learning Techniques ◽  
Soft Computing Techniques ◽  
The One

Structural Health Monitoring (SHM) allows us to have information about the structure under investigation and thus to create analytical models for the assessment of its state or structural behavior. Exceeded a predetermined danger threshold, the possibility of an early warning would allow us, on the one hand, to suspend risky activities and, on the other, to reduce maintenance costs. The system proposed in this paper represents an integration of multiple traditional systems that integrate data of a different nature (used in the preventive phase to define the various behavior scenarios on the structural model), and then reworking them through machine learning techniques, in order to obtain values to compare with limit thresholds. The risk level depends on several variables, specifically, the paper wants to evaluate the possibility of predicting the structure behavior monitoring only displacement data, transmitted through an experimental transmission control unit. In order to monitor and to make our cities more “sustainable”, the paper describes some tests on road infrastructure, in this contest through the combination of geomatics techniques and soft computing.

A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms

2020 ◽  
pp. 1851-1885
Author(s):  
Bilal Ervural ◽  
Beyzanur Cayir Ervural ◽  
Cengiz Kahraman
Keyword(s):  
Soft Computing ◽  
Bat Algorithm ◽  
Computing Methods ◽  
Analytical Models ◽  
Grey Wolf Optimizer ◽  
Particle Swarm Algorithm ◽  
Bee Colony ◽  
Soft Computing Techniques ◽  
Soft Computing Methods ◽  
Firefly Optimization

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.

scholarly journals Comparative analysis of design models for concrete corbels

2016 ◽  
Vol 9 (3) ◽  
pp. 435-470
Author(s):  
D. L. Araújo ◽  
A. P. Silva Neto ◽  
F. A. Lobo ◽  
M. K. El Debs
Keyword(s):  
Comparative Analysis ◽  
Failure Load ◽  
Precast Concrete ◽  
Analytical Models ◽  
Test Results ◽  
Statistical Tools ◽  
Design Models ◽  
Eurocode 2

ABSTRACT The main objective of this paper is performing a comparative analysis of some design models for precast concrete corbels. For this, it was analyzed design models from Brazilian (NBR 9062) and European (EUROCODE 2) Codes and a US design handbook (PCI). Moreover, three analytical models showed in the literature are analyzed. The objective of this comparative is identifying the best design models to represent the failure load of concrete corbels by the tie yields or by the concrete crushing. Moreover, it is intended to evaluate the contribution of horizontal stirrups to resistance of concrete corbels. For this, a database was assembled from test results of concrete corbels carried out by several researchers and they are showed in the literature. The design models were applied to this database and from statistical tools, adjustments coefficients are recommended to be applied on these design models to take into account the results dispersion found in the analysis.

A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms

2017 ◽  
pp. 34-68
Author(s):  
Bilal Ervural ◽  
Beyzanur Cayir Ervural ◽  
Cengiz Kahraman
Keyword(s):  
Soft Computing ◽  
Bat Algorithm ◽  
Computing Methods ◽  
Analytical Models ◽  
Grey Wolf Optimizer ◽  
Particle Swarm Algorithm ◽  
Bee Colony ◽  
Soft Computing Techniques ◽  
Soft Computing Methods ◽  
Firefly Optimization

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.

Soft Computing in Electromagnetics

2015 ◽  
Author(s):  
Balamati Choudhury ◽  
Rakesh Mohan Jha
Keyword(s):  
Soft Computing

Mechanism of irregular crack-propagation in thermal controlled fracture of ceramics induced by microwave

2020 ◽  
Vol 21 (6) ◽  
pp. 610
Author(s):  
Xiaoliang Cheng ◽  
Chunyang Zhao ◽  
Hailong Wang ◽  
Yang Wang ◽  
Zhenlong Wang
Keyword(s):  
Crack Propagation ◽  
Industrial Application ◽  
Ceramic Materials ◽  
Advanced Technology ◽  
Analytical Models ◽  
Propagation Mechanism ◽  
Unstable Crack ◽  
Fracture Simulation ◽  
Initial Stage ◽  
Controlled Fracture

Microwave cutting glass and ceramics based on thermal controlled fracture method has gained much attention recently for its advantages in lower energy-consumption and higher efficiency than conventional processing method. However, the irregular crack-propagation is problematic in this procedure, which hinders the industrial application of this advanced technology. In this study, the irregular crack-propagation is summarized as the unstable propagation in the initial stage, the deviated propagation in the middle stage, and the non-penetrating propagation in the end segment based on experimental work. Method for predicting the unstable propagation in the initial stage has been developed by combining analytical models with thermal-fracture simulation. Experimental results show good agreement with the prediction results, and the relative deviation between them can be <5% in cutting of some ceramics. The mechanism of deviated propagation and the non-penetrating propagation have been revealed by simulation and theoretical analysis. Since this study provides effective methods to predict unstable crack-propagation in the initial stage and understand the irregular propagation mechanism in the whole crack-propagation stage in microwave cutting ceramics, it is of great significance to the industrial application of thermal controlled fracture method for cutting ceramic materials using microwave.

Classifying the Past: Discriminant Analysis and its Application to Medieval Farming Systems

1996 ◽  
Vol 8 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ken Bartley
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Processing Time ◽  
Farming Systems ◽  
Frame Of Reference ◽  
Analytical Models ◽  
Successful Implementation ◽  
Medieval Period ◽  
The Past ◽  
Livestock Management

This paper discusses the need for nationally based analytical models of the medieval period. The use of cluster analysis as a method for classifying demesne farms, by the crops they grew and their livestock management, is explained. Successful implementation of cluster analysis requires both the existence of a large base sample, to permit isolation of specific groupings within the data, and access to considerable processing time. The paper concludes by demonstrating how discriminant analysis can provide an efficient and systematic way of classifying even a single manor within a national frame of reference.

MACHINE LEARNING FOR SOFTWARE

2019 ◽  
pp. 251-255
Author(s):  
Shafagat Mahmudova
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Soft Computing ◽  
Computing Technology

The study machine learning for software based on Soft Computing technology. It analyzes Soft Computing components. Their use in software, their advantages and challenges are studied. Machine learning and its features are highlighted. The functions and features of neural networks are clarified, and recommendations were given.

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