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检索条件"任意字段=2nd International Conference on Soft Computing and its Engineering Applications, icSoftComp 2020"

共 192 条记录，以下是1-10 订阅

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2nd international conference on soft computing and its engineering applications, icsoftcomp 2020

2nd International Conference on Soft Computing and its Engin...

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2nd international conference on soft computing and its engineering applications, icsoftcomp 2020

ISBN: (纸本)9789811607073

The proceedings contain 28 papers. The special focus in this conference is on soft computing and its engineering applications. The topics include: Rethinking the Limits of Optimization Economic Order Quantity (EOQ) Using Self Generating Training Model by Adaptive-Neuro Fuzzy Inference System;Hybrid POS Tagger for Gujarati Text;Optimization of ICT Street Infrastructure in Smart Cities;transfer Learning-Based Image Tagging Using Word Embedding Technique for Image Retrieval applications;comparison of Deep Learning Models for Cancer Metastases Detection: An Experimental Study;a Lightweight Hybrid Majority Vote Classifier Using Top-k Dataset;twitter Emotion Analysis for Brand Comparison Using Naive Bayes Classifier;a Smart Card Based Lightweight Multi Server Encryption Scheme;Firmware Attack Detection on Gadgets Using Ridge Regression (FAD-RR);Automatic Image Colorization Using GANs;automatic Text Extraction from Digital Brochures: Achieving Competitiveness for Mauritius Supermarkets;improved Predictive System for Soil Test Fertility Performance Using Fuzzy Rule Approach;Artificial Intelligence applications to Tackle COVID-19;throat Inflammation Based Mass Screening of Covid-19 on Embedded Platform;predicting Novel CoronaVirus 2019 with Machine Learning Algorithms;evaluation of Image Filtering Parameters for Plant Biometrics Improvement Using Machine Learning;Glaucoma Detection Using Features of Optic Nerve Head, CDR and ISNT from Fundus Image of Eye;crop Yield Estimation Using Machine Learning;embedded Linux Based Smart Secure IoT Intruder Alarm System Implemented on BeagleBone Black;gujarati Task Oriented Dialogue Slot Tagging Using Deep Neural Network Models;energy Efficient Aspects of Federated Learning – Mechanisms and Opportunities;classification of UrbanSound8k: A Study Using Convolutional Neural Network and Multiple Data Augmentation Techniques.

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Three Languages Simulate Polygons and Perform on the Web Python, Fortran, C, with PHP and 'gnuplot' 5th

Three Languages Simulate Polygons and Perform on the Web Pyt...

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5th international conference on soft computing and its engineering applications (icsoftcomp)

作者： Casquilho, Miguel Pacheco, Pedro Univ Lisbon Dept Chem Engn IST Lisbon Portugal CERENA Ctr Nat Resources & Environm Lisbon Portugal Univ Lisbon Dept Comp Sci & Engn IST Lisbon Portugal

ISBN: (纸本)9783031537271;9783031537288

On a web page, we display, resorting to the Monte Carlo method, the statistical behavior of the perimeter and area of random polygons inscribed in a circle. We obtain three outcomes: those variables behave surprisingly, mainly the perimeter;three languages run at very different speeds, which is expected, but notorious;and the web page is an example of what can be simply done on the Web. The web page is of free access to a user through the use of a browser, thus without any software installation and necessitating no particular power or matching operating system. This is an illustrative example making it possible to ready adaptation to a number of other problems. It combines the Web and convenient computer languages, to wit: PHP, Python, Fortran, and C, and the 'gnuplot' utility for plotting. The study has as objectives: to observe the said behaviors;to serve as a model to solve other problems;and, more generally, to call attention both to the Web as a medium for scientific computing, and to the adequacy of this in scientific publications. This study recommends computing in a web-based style, in general, which can use executable programs mostly similar to classical computing, these being the inevitable difficulty. This scarcely explored approach is promptly accessed here, and invites the cooperation of academia and industry in our technological era.

关键词： Web-based computing random generated polygons computing in Science and Technology engineering education Statistical applications

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Embracing Uncertainty and Approximations for Intelligent Problem-Solving with soft computing 2

Embracing Uncertainty and Approximations for Intelligent Pro...

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2nd IEEE international conference on Trends in Quantum computing and Emerging Business Technologies, TQCEBT 2024

作者： Dodamani, Abeda Sultan Ghori, Md. Atheeq Patel, Jaksan D Sathish Kumar, R. Dharamvir, Dharamvir Kumar, Narendra University of Eswatini Faculty of Science and Technology Department of Mathematics KwaluseniEswatini M201 India Telangana University Nizamabad Department of Computer Science and Engineering Telangana State India Merchant Engineering College Mechanical Engineering Basna Gujarat Mehsana India Jain University Faculty of Engineering and Technology Department of Aiml Karnataka Bengaluru562112 India The Oxford College of Engineering Department of Mca Bengaluru560100 India Czestochowa University of Technology Poland

ISBN: (纸本)9798350384277

Unlike traditional computing, soft computing solves difficult real-world problems and works with approximation models. soft computing is more forgiving of approximations, ambiguity, partial truth, and imprecision than hard computing. The human mind is, in a sense, the ideal model for soft computing. Techniques like fuzzy logic, machine learning, genetic algorithms, expert systems, and artificial neural networks are the foundation of soft computing. Even though soft computing theory and methods were initially presented in the 1980s, automatic control engineering currently uses them as a major area of research and study. soft computing techniques are currently being successfully applied in a wide range of commercial, industrial, and household applications. soft computing techniques and application areas are expected to grow further with the introduction of low-cost, outstanding-performance digital processing units and the falling cost of memory chips. The purpose of this paper is to discuss embracing uncertainties and approximation for intelligent problem-solving with the help of soft computing. First, the study has discussed various soft computing systems. Moreover, the concept of fuzzy logic has been illustrated along with a description of its applications. In terms of research methodology, this research paper has followed a qualitative research approach by gathering knowledge based on reviewing a wide range of different studies regarding the research topic. According to the findings of this research, as computer processing units get cheaper and more powerful, intelligent systems and soft computing techniques become more significant. Complex algorithms must be used by intelligent systems to make difficult judgments and select the optimal solution from a range of options. © 2024 IEEE.

关键词： Expert systems

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A Comprehensive Portrayal of Research Drifts in Islanding Detection Methods towards soft computing 2

A Comprehensive Portrayal of Research Drifts in Islanding De...

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2nd international conference on Power Electronics and IoT applications in Renewable Energy and its Control, PARC 2022

作者： Bhushan, Indu Chandra, Subhash Yadav, Aravind Institute of Engineering Technology GLA Mathura India

ISBN: (纸本)9781665432153

This paper represents survey of various signal processing advancement and supported soft computing techniques for detecting islanding disturbances that occur in distributed generation (DG) based power system which is interconnected. Variety of latent islanding procedures, for example, Under/Over Voltage and Under/Over recurrence, Voltage Phase Jump Detection, Harmonic estimation, Voltage unbalance and so on are examined broadly for distinguishing proof of islanding situations. Further, progressed signal preparing, and delicate registering procedures are being examined for recognition or recognizing objectives and are being thought or ruminated about. It is featured that the sign handling and delicate processing strategies give quicker recognition with non-discovery zone (ndZ). These procedures are seen to be stronger and more adaptable in managing complex nonlinear frameworks. An examination review between the distinctive islanding methods is or has been introduced to know various merits and demerits of each. Advancing it with support to soft computing technique in islanding detection. © 2022 IEEE.

关键词： soft computing

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ResNet-50: The Deep Networks for Automated Breast Cancer Classification using MR Images 2

ResNet-50: The Deep Networks for Automated Breast Cancer Cla...

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2nd international conference on Advancements in Smart, Secure and Intelligent computing, ASSIC 2024

作者： Das, Tejaswini Nayak, Debasish Swapnesh Kumar Kar, Anindita Jena, Lambodar Swarnkar, Tripti University Dept. of Computer Application FET-ITER Bhubaneswar India University FET-ITER Dept. of Computer Science and Engineering Bhubaneswar India Bhubaneswar India

ISBN: (纸本)9798350370188

One in every four cancer cases in women is breast cancer, which is the most prevalent malignancy in this group globally. In 2020, breast cancer will account for one in every eight new instances of cancer, according to projections of 2.3 million new cases. Breast cancer identification, both early and accurate, is critical to improve patient outcomes and survival rates. Magnetic resonance imaging (MRI) has developed as a valuable method for diagnosing breast cancer. Deep learning algorithms, notably convolutional neural networks (CNNs), have demonstrated exceptional effectiveness in a variety of medical image processing applications, including breast cancer classification. The ResNet-50 architecture has received a lot of interest in this context because of its excellent performance in image recognition tasks. ResNet-50 is a deep residual network that introduces skip connections and residual learning to solve the difficulty of training very deep neural networks. A total number of 1480 cancer MRI samples are collected from the Kaggle database, having two classes, which include healthy and malignant scans. It is observed that our proposed model with the data pre-processing techniques has achieved a classification accuracy of 92.01%. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Design of LLC Resonant Converter for EV Charging Using Neural Network-Based PI Controller 1

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2nd international conference on Intelligent computing Systems and applications, ICICSA 2023

作者： Lakshmi, Royyuru Manasa Chandrakala, K. R. M. Vijaya Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9789819754120

ISBN: (纸本)9789819754113

The proposed work presents the design and modeling of an LLC converter for electric vehicle battery charging applications, specifically using a 12 V lead-acid battery output. The LLC converter has opted for its soft switching characteristics, ability to produce smooth waveforms, high power density, low electromagnetic interference, and high efficiency, which are desirable for electric vehicle battery charging. The design process includes establishing the suitable transformer turns ratio and selecting resonant tank components such as the resonant inductor, resonant capacitor, and magnetizing inductor. These choices are critical for achieving optimal performance in the LLC converter. Furthermore, this work explores the implementation of closed loop control using a neural network controller. The advantages of neural networks, such as improved control performance and adaptability, are discussed. MATLAB/SIMULINK software is utilized to simulate the LLC converter, and the results demonstrate the benefits of employing a neural network-based controller. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electric vehicle LLC resonant converter Neural network controller

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Envisioning the Future of Robotics Sensors: Innovations and Prospects 2nd

Envisioning the Future of Robotics Sensors: Innovations and ...

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2nd international conference on Futuristic Advancements in Materials, Manufacturing, and Thermal Sciences, ICFAMMT 2024

作者： Mahadik, Shrikant C. Deulgaonkar, Vikas R. Bhosle, Sachin M. Dhamdhere, Onkar A. Taware, Nikhil S. Darade, Nikhil D. Gadhave, Ganesh J. Department of Mechanical Engineering Vishwakarma Institute of Information Technology Kondhwa Pune India Department of Mechanical Engineering Marathwada Mitra Mandal’s College of Engineering Pune India Department of Mechanical Engineering Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering & Technology Baramati Pune India

ISBN: (纸本)9789819756209

Article navigates the future trajectory of robotics sensors, envisioning an era marked by transformative technologies that redefine the capabilities of robotic systems. Emphasizing the pivotal role of sensors in shaping robotics, exploring the current state, spotlighting challenges that upcoming technologies seek to overcome. Detailed investigations of key technological trends, including advanced vision systems and sensor fusion, uncover promising developments like high-resolution cameras, 3D imaging, and hyperspectral sensors, fostering a nuanced environmental understanding. Emerging technologies like LiDAR, solid-state LiDAR, photonics, and flexible sensors unlock potential applications in soft robotics and wearables. Neuromorphic sensors, inspired by the human brain, hold promise for revolutionizing robotic perception and decision-making. Delving into the integration of artificial intelligence with sensors, exploring its impact on real-time decision-making and the evolving shift toward edge computing, emphasizing gains in speed, efficiency, and privacy. applications in autonomous systems, self-driving cars, drones, and human–robot collaboration are dissected, concluding with an examination of challenges, privacy concerns, and ethical considerations. This paper underscores the imperative for responsible development and deployment, summarizing key technologies that bear the potential to reshape the future of robotics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Hyperspectral imaging

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soft computing Application in Electrical, Electronics and Communication Field 2

Soft Computing Application in Electrical, Electronics and Co...

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2nd IEEE international conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Jindal, Ruby Yadav, Renu Singh, Dharmendra Kumar, R. Gowtham, M.S. Birare, Komal Madhukar School of Basic & Applied Sciences K. R. Mangalam University Department of Physics Haryana Gurugram122103 India Electronics and Communications Engineering Dev Bhoomi Uttarakhand University Uttarakhand 248007 India Invertis University Department of Applied Sciences Uttar Pradesh Bareilly243123 India Karpagam Academy of Higher Education Department of Chemistry Coimbatore641021 India Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore641105 India It Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350369960

The term 'soft technologies' signifies a school of thought, rational thought, and explanation that acknowledges the practical benefits of combining, giving in, including categorising several variables during an investigation that takes shape in actuality. its capacity to control intricate structures is despite the fact that it derives primarily feelings defined without exact verifiable designation set limitations for each component. It varies with difficult technologies because it is not as forgiving of errors, uncertainties, and unfinished data. In reality, IT constructs an environment using how people think. Using an allowance for mistake, unknowns, as well as limited truth to promote tractability, flexibility, and low reaction expense is the fundamental tenet of computers. Technologies primary methods includes Bayesian analysis of information, neural networks, inaccurate mathematics, and Darwinian computations. Although certain strategies may be employed alone, a few of the key advantages of computer science is that each approach complements the others. Mixing methodologies can offer answers to issues which conventional strategies have proved incapable to tackle due to the fact that become overly complicated or intrinsically unstable. Some key benefits of smart applications for robotics were evident. It seemed feasible to address challenging issues early on despite using computer-based techniques. It also contributed to the introduction of human wisdom in a variety of computing domains, including thinking, praise, comprehension, education, among a host of more. It was possible to create complicated equipment as an outcome, including electronics planning programmes and autonomously self-tuning equipment. The present piece emphasises a number of different themes. © 2023 IEEE.

关键词： Fuzzy Logic Neuro computing soft computing

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Multi-Objective Optimization Technique Based Design of Squirrel Cage Induction Motor 2

Multi-Objective Optimization Technique Based Design of Squir...

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2nd international conference on Power Electronics and IoT applications in Renewable Energy and its Control, PARC 2022

作者： Tripathy, Surya Narayan Kundu, Shubhasri Pradhan, Arjyadharan Kalinga Institute of Industrial Technology School of Electrical Engineering Bhubaneswar India

ISBN: (纸本)9781665432153

Induction motors are widely used in industries because of their rugged construction and simple operation. Owing to their relatively low cost, reliability and efficiency, 80% of the electrical motors are the three-phase squirrel cage induction motors (SCIMs). In most industries, they are the main energy consuming devices, contributing to more than 80% of electromechanical energy consumption. The objective of the present research is to develop novel parameter optimization technique by applying soft computing algorithms such as Genetic Algorithm (GA) and Particle Swarm optimization (PSO) for optimal design of different types of induction. It will not only improve the efficiency of motor but also improve the power factor. Here two objectives are taken simultaneously for the optimization, but the involvement of two mutually contradictory objective functions makes the current optimization problem as multi-objective one. The multi-objective optimization problem is converted into single objective problem by giving different weights to each objective according to the priority of the objective functions. The results obtained from the optimization are the non-dominated solutions, which forms a pareto curve. Every point in the pareto curve is a solution for the problem, we have to select one solution depending upon our *** design parameters obtained from the conventional design technique and the performance of all the proposed techniques are compared. The improvement in performance is achieved by reducing the variable losses occurred in the motor by suitable design. To validate the objective of research, different stator and rotor winding configurations have been attempted on 7.5 kW three phase Squirrel Cage Induction Motor (SCIM). © 2022 IEEE.

关键词： Genetic algorithms

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Automatic Image Colorization Using GANs 2nd

Automatic Image Colorization Using GANs

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2nd international conference on soft computing and its engineering applications, icsoftcomp 2020

作者： Dhir, Rashi Ashok, Meghna Gite, Shilpa Kotecha, Ketan Symbiosis International University Near Lupin Research Park Lavale Mulshi Pune Maharashtra India Symbiosis International University Near Lupin Research Park Lavale Mulshi Pune Maharashtra India

ISBN: (纸本)9789811607073

Automatic image colorization as a process has been studied extensively over the past 10 years with importance given to its many applications in grayscale image colorization, aged/degraded image restoration etc. In our project, we aim to generalize this process using a Generative Adversarial Network (GAN) that takes fixed size black and white images as input and obtains corresponding coloured images of the same size as output, to demonstrate GAN working and superiority. We use a special type of GAN called Conditional Generative Adversarial Network which takes a specific type of input as opposed to vectors from random probability distributions, and we primarily work on the CIFAR-10 dataset. Our goal was to build a successful CGAN model using limited resources that utilizes Google Colaboratory, Strided Convolutions and Batch Normalization to colorize images. Our resulting model is essentially a base model that beginners and students can implement and embellish to further GAN understanding and techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Generative adversarial networks

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