IMPLEMENTATION OF COMPUTATIONAL INTELLIGENCE OPTIMIZATION TECHNIQUES TO EXTRICATE VARIANT OF VRP

2020 ◽  
Vol 9 (8) ◽  
pp. 5581-5591
Author(s):  
Mini ◽  
A. Pal
Keyword(s):  
Computational Intelligence ◽  
Optimization Techniques

Computational Intelligence-Based Cell Nuclei Segmentation from Pap Smear Images

2016 ◽  
pp. 262-284
Author(s):  
Savitha Balakrishnan ◽  
Subashini Parthasarathy ◽  
Krishnaveni Marimuthu
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Computational Intelligence ◽  
Pap Smear ◽  
Correct Diagnosis ◽  
Optimization Techniques ◽  
Cell Nuclei ◽  
Swarm Optimization ◽  
Nuclei Segmentation ◽  
Segmentation Problem

Automated Segmentation of cell nuclei in Pap smear images plays an important role in the cervical cancer cell analysis systems to make a correct diagnosis decision. The aim of this chapter is to detail about the variety of computational intelligence and image processing approaches developed and used for the nuclei segmentation. In additional, the threshold based segmentation problem is treated as an optimization problem with an objective of preserving both the size and volume of the cell nuclei and also to segment the nuclei region from the original microscopic Pap smear image with the help of Particle Swarm Optimization (PSO) and Ant Colony Optimization techniques (ACO). Experimental results are shown, compared in quantitative and qualitative manner as well as the main advantages and limitations of each algorithm are explained.

scholarly journals Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4063 ◽  
Author(s):  
Touqeer Ahmed Jumani ◽  
Mohd Wazir Mustafa ◽  
Nawaf N. Hamadneh ◽  
Samer H. Atawneh ◽  
Madihah Md. Rasid ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Power Quality ◽  
Computational Intelligence ◽  
Research Work ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Inference System ◽  
Study Objective ◽  
Comprehensive Review

The penetration of distributed generators (DGs) in the existing power system has brought some real challenges regarding the power quality and dynamic response of the power systems. To overcome the above-mentioned issues, the researchers around the world have tried and tested different control methods among which the computational intelligence (CI) based methods have been found as most effective in mitigating the power quality and transient response problems intuitively. The significance of the mentioned optimization approaches in contemporary ac Microgrid (MG) controls can be observed from the increasing number of published articles and book chapters in the recent past. However, literature related to this important subject is scattered with no comprehensive review that provides detailed insight information on this substantial development. As such, this research work provides a detailed overview of four of the most extensively used CI-based optimization techniques, namely, artificial neural network (ANN), fuzzy logic (FL), adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) as applied in ac MG controls from 42 research articles along with their basic working mechanism, merits, and limitations. Due to space and scope constraints, this study excludes the applications of swarm intelligence-based optimization methods in the studied field of research. Each of the mentioned CI algorithms is explored for three major MG control applications i.e., reactive power compensation and power quality, MPPT and MG’s voltage, frequency, and power regulation. In addition, this work provides a classification of the mentioned CI-based optimization studies based on various categories such as key study objective, optimization method applied, DGs utilized, studied MG operating mode, and considered operating conditions in order to ease the searchability and selectivity of the articles for the readers. Hence, it is envisaged that this comprehensive review will provide a valuable one-stop source of knowledge to the researchers working in the field of CI-based ac MG control architectures.

Computational Intelligence-Based Cell Nuclei Segmentation from Pap Smear Images

Biometrics ◽  
2017 ◽  
pp. 259-280
Author(s):  
Savitha Balakrishnan ◽  
Subashini Parthasarathy ◽  
Krishnaveni Marimuthu
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Computational Intelligence ◽  
Pap Smear ◽  
Correct Diagnosis ◽  
Optimization Techniques ◽  
Cell Nuclei ◽  
Swarm Optimization ◽  
Nuclei Segmentation ◽  
Segmentation Problem

Automated Segmentation of cell nuclei in Pap smear images plays an important role in the cervical cancer cell analysis systems to make a correct diagnosis decision. The aim of this chapter is to detail about the variety of computational intelligence and image processing approaches developed and used for the nuclei segmentation. In additional, the threshold based segmentation problem is treated as an optimization problem with an objective of preserving both the size and volume of the cell nuclei and also to segment the nuclei region from the original microscopic Pap smear image with the help of Particle Swarm Optimization (PSO) and Ant Colony Optimization techniques (ACO). Experimental results are shown, compared in quantitative and qualitative manner as well as the main advantages and limitations of each algorithm are explained.

Review on the aerodynamics of intermediate compressor duct

2020 ◽  
Vol 14 (4) ◽  
pp. 7446-7468
Author(s):  
Manish Sharma ◽  
Beena D. Baloni
Keyword(s):  
High Pressure ◽  
Pressure Loss ◽  
Flow Analysis ◽  
Outer Wall ◽  
Optimization Techniques ◽  
Optimum Pressure ◽  
Research Areas ◽  
Static Pressure Distribution ◽  
High Pressure Compressor ◽  
Pressure Compressor

In a turbofan engine, the air is brought from the low to the high-pressure compressor through an intermediate compressor duct. Weight and design space limitations impel to its design as an S-shaped. Despite it, the intermediate duct has to guide the flow carefully to the high-pressure compressor without disturbances and flow separations hence, flow analysis within the duct has been attractive to the researchers ever since its inception. Consequently, a number of researchers and experimentalists from the aerospace industry could not keep themselves away from this research. Further demand for increasing by-pass ratio will change the shape and weight of the duct that uplift encourages them to continue research in this field. Innumerable studies related to S-shaped duct have proven that its performance depends on many factors like curvature, upstream compressor’s vortices, swirl, insertion of struts, geometrical aspects, Mach number and many more. The application of flow control devices, wall shape optimization techniques, and integrated concepts lead a better system performance and shorten the duct length.  This review paper is an endeavor to encapsulate all the above aspects and finally, it can be concluded that the intermediate duct is a key component to keep the overall weight and specific fuel consumption low. The shape and curvature of the duct significantly affect the pressure distortion. The wall static pressure distribution along the inner wall significantly higher than that of the outer wall. Duct pressure loss enhances with the aggressive design of duct, incursion of struts, thick inlet boundary layer and higher swirl at the inlet. Thus, one should focus on research areas for better aerodynamic effects of the above parameters which give duct design with optimum pressure loss and non-uniformity within the duct.

Application of Computational Mechanics to Tire Design—Yesterday, Today, and Tomorrow

2011 ◽  
Vol 39 (4) ◽  
pp. 223-244 ◽  
Author(s):  
Y. Nakajima
Keyword(s):  
Finite Element ◽  
New Technologies ◽  
Computational Mechanics ◽  
Design Procedure ◽  
Side Wall ◽  
Rolling Resistance ◽  
Optimization Techniques ◽  
Stress Strain ◽  
Element Analysis ◽  
Crown Shape

Abstract The tire technology related with the computational mechanics is reviewed from the standpoint of yesterday, today, and tomorrow. Yesterday: A finite element method was developed in the 1950s as a tool of computational mechanics. In the tire manufacturers, finite element analysis (FEA) was started applying to a tire analysis in the beginning of 1970s and this was much earlier than the vehicle industry, electric industry, and others. The main reason was that construction and configurations of a tire were so complicated that analytical approach could not solve many problems related with tire mechanics. Since commercial software was not so popular in 1970s, in-house axisymmetric codes were developed for three kinds of application such as stress/strain, heat conduction, and modal analysis. Since FEA could make the stress/strain visible in a tire, the application area was mainly tire durability. Today: combining FEA with optimization techniques, the tire design procedure is drastically changed in side wall shape, tire crown shape, pitch variation, tire pattern, etc. So the computational mechanics becomes an indispensable tool for tire industry. Furthermore, an insight to improve tire performance is obtained from the optimized solution and the new technologies were created from the insight. Then, FEA is applied to various areas such as hydroplaning and snow traction based on the formulation of fluid–tire interaction. Since the computational mechanics enables us to see what we could not see, new tire patterns were developed by seeing the streamline in tire contact area and shear stress in snow in traction.Tomorrow: The computational mechanics will be applied in multidisciplinary areas and nano-scale areas to create new technologies. The environmental subjects will be more important such as rolling resistance, noise and wear.

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