Archives of Computational Methods in Engineering

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A First Step Towards the Use of Proper General Decomposition Method for Structural Optimization
Archives of Computational Methods in Engineering - Tập 17 - Trang 465-472 - 2010
A. Leygue, E. Verron
In structural optimization, the implicit nature of the cost function with respect to the optimization parameters, i.e. through the solution of the structural problem calculated with fixed values of these parameters, leads to prohibitive computations whatever the adopted formulation. Consequently, it yields limitations in both the number of parameters and the size of the structural problem. Moreove... hiện toàn bộ
Nature-Inspired Optimization Algorithms in Solving Partial Shading Problems: A Systematic Review
Archives of Computational Methods in Engineering - Tập 30 - Trang 223-249 - 2022
Clifford Choe Wei Chang, Tan Jian Ding, Mohammad Arif Sobhan Bhuiyan, Kang Chia Chao, Mohammadmahdi Ariannejad, Haw Choon Yian
Artificial intelligence based maximum power point tracking (MPPT) techniques play an essential role in improving the efficiency of photovoltaic power conversion systems. Over the past few years, researchers around the world have proposed various nature-inspired metaheuristic optimization algorithms in order to extract the highest possible power from photovoltaic (PV) systems under partial shading ... hiện toàn bộ
Comprehensive Review of Orthogonal Regression and Its Applications in Different Domains
Archives of Computational Methods in Engineering - Tập 29 - Trang 4027-4047 - 2022
Pallavi, Sandeep Joshi, Dilbag Singh, Manjit Kaur, Heung-No Lee
Orthogonal regression is one of the prominent approaches for linear regression used to adjust the estimate of predictor errors. It can be considered as a least square regression with orthogonal constraints. It can maintain more discriminative constraints in the projection subspace than the least square regression and can avoid trivial solutions. In contrast to basic linear regression, orthogonal r... hiện toàn bộ
Systematic Fitting and Comparison of Hyperelastic Continuum Models for Elastomers
Archives of Computational Methods in Engineering - Tập 30 - Trang 2257-2288 - 2023
Alexander Ricker, Peter Wriggers
Hyperelasticity is a common modeling approach to reproduce the nonlinear mechanical behavior of rubber materials at finite deformations. It is not only employed for stand-alone, purely elastic models but also within more sophisticated frameworks like viscoelasticity or Mullins-type softening. The choice of an appropriate strain energy function and identification of its parameters is of particular ... hiện toàn bộ
Automatic Speech Recognition System for Tonal Languages: State-of-the-Art Survey
Archives of Computational Methods in Engineering - Tập 28 - Trang 1039-1068 - 2020
Jaspreet Kaur, Amitoj Singh, Virender Kadyan
Natural language and human–machine interaction is a very much traversed as well as challenging research domain. However, the main objective is of getting the system that can communicate in well-organized manner with the human, regardless of operational environment. In this paper a systematic survey on Automatic Speech Recognition (ASR) for tonal languages spoken around the globe is carried out. Th... hiện toàn bộ
A Review on Computational Methods for Denoising and Detecting ECG Signals to Detect Cardiovascular Diseases
Archives of Computational Methods in Engineering - Tập 29 - Trang 1875-1914 - 2021
Prashant Mani Tripathi, Ashish Kumar, Rama Komaragiri, Manjeet Kumar
Cardiac health of the human heart is an intriguing issue for many decades as cardiovascular diseases (CVDs) are the leading cause of death worldwide. Electrocardiogram (ECG) signal is a powerful complete non-invasive tool for analyzing cardiac health. ECG signal is the primary choice of various health practitioners to determine vital information about the human heart. In the literature, the ECG si... hiện toàn bộ
A Structured Analysis to study the Role of Machine Learning and Deep Learning in The Healthcare Sector with Big Data Analytics
Archives of Computational Methods in Engineering - Tập 30 - Trang 3673-3701 - 2023
Juli Kumari, Ela Kumar, Deepak Kumar
Machine and deep learning are used worldwide. Machine Learning (ML) and Deep Learning (DL) are playing an increasingly important role in the healthcare sector, particularly when combined with big data analytics. Some of the ways that ML and DL are being used in healthcare include Predictive Analytics, Medical Image Analysis, Drug Discovery, Personalized Medicine, and Electronic Health Records (EHR... hiện toàn bộ
Deep Learning Challenges and Prospects in Wireless Sensor Network Deployment
Archives of Computational Methods in Engineering - - 2024
Yaner Qiu, Liyun Ma, Rahul Priyadarshi
This paper explores the transformative integration of deep learning applications in the deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in diverse domains, the infusion of deep learning techniques offers unprecedented opportunities for enhanced data processing, analysis, and decision-making. The research problem addressed in this paper revolves around navigat... hiện toàn bộ
A Comprehensive Survey on the Recent Variants and Applications of Membrane-Inspired Evolutionary Algorithms
Archives of Computational Methods in Engineering - Tập 29 - Trang 3041-3057 - 2022
Bisan Alsalibi, Seyedali Mirjalili, Laith Abualigah, Rafaa Ismael yahya, Amir H. Gandomi
In the last decade, the application of membrane-inspired evolutionary algorithms in real-life problems has attracted much attention due to their flexibility and parallelizability. Almost seven years have passed since the first membrane algorithms survey paper was published in 2014. Considering the importance and ongoing research on such algorithms and their applications in various disciplines, thi... hiện toàn bộ
Correction to: The Emerging Trends of Quantum Computing Towards Data Security and Key Management
Archives of Computational Methods in Engineering - Tập 28 - Trang 5035-5035 - 2021
Neha Sharma, Ramkumar Ketti Ramachandran
A correction to this paper has been published: https://doi.org/10.1007/s11831-021-09592-9
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