Archives of Computational Methods in Engineering最新文献

A Survey of Artificial Intelligence Applications in Wind Energy Forecasting 人工智能在风能预测中的应用调查

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-13 DOI: 10.1007/s11831-024-10182-8

Poonam Dhaka, Mini Sreejeth, M. M. Tripathi

引用次数: 0

Biomechanical Properties of the Large Intestine 大肠的生物力学特性

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-10 DOI: 10.1007/s11831-024-10177-5

Minghui Wang, Ji Liu, Taiyu Han, Wei Zhou, Yuhui Zhou, Hongliu Yu

{"title":"Biomechanical Properties of the Large Intestine","authors":"Minghui Wang, Ji Liu, Taiyu Han, Wei Zhou, Yuhui Zhou, Hongliu Yu","doi":"10.1007/s11831-024-10177-5","DOIUrl":"https://doi.org/10.1007/s11831-024-10177-5","url":null,"abstract":"The large intestine is an important part of the human digestive system and the target of many diseases. The biomechanical properties of the large intestine are closely related to the proper functioning of its mechanical behavior. Therefore, the study of its biomechanical properties can help to better understand the key factors of lesions and provide a theoretical basis for the research and application of disease treatment, artificial anal sphincter, and other related medical devices. Physiologic structure of the large intestine is the basis for the study of its biomechanical properties. Constitutive models are commonly used to describe the biomechanical properties of soft tissues and to provide a mathematical characterization of the effects of biological components on the behavior of materials. The studies and results of biomechanical experiments provide a basis for determining the material parameters and the causes of functional damage to the material. In this paper, the biomechanical properties of the large intestine are investigated from two aspects: active properties and passive properties, and three perspectives: physiological structure, constitutive models, and biomechanical experiments. The paper concludes that their effective combination is an important comprehensive method to study the biomechanical properties of the large intestine. It provides a new perspective for the study of biomechanical properties of the large intestine, and provides a theoretical basis for future related biomechanical studies and the development of related medical devices.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"1 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-objective Ant Colony Optimization: Review 多目标蚁群优化：回顾

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-10 DOI: 10.1007/s11831-024-10178-4

Mohammed A. Awadallah, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Lamees Mohammad Dalbah, Aneesa Al-Redhaei, Shaimaa Kouka, Oussama S. Enshassi

{"title":"Multi-objective Ant Colony Optimization: Review","authors":"Mohammed A. Awadallah, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Lamees Mohammad Dalbah, Aneesa Al-Redhaei, Shaimaa Kouka, Oussama S. Enshassi","doi":"10.1007/s11831-024-10178-4","DOIUrl":"https://doi.org/10.1007/s11831-024-10178-4","url":null,"abstract":"Ant colony optimization (ACO) algorithm is one of the most popular swarm-based algorithms inspired by the behavior of an ant colony to find the shortest path for food. The multi-objective ACO (MOACO) is a modified variant of ACO introduced to deal with multi-objective optimization problems (MOPs). The MOACO is seeking to find a set of solutions that achieve trade-offs between the different objectives, which help the decision-makers select the most appreciated solution according to their preferences. Recently, a large number of MOACO research works have been published in the literature, reaching 384 research papers according to the SCOPUS database. In this review paper, 189 different research works of MOACOs published in only scientific journals are considered. Through this research, researchers will gain insights into the expansion of MOACO, the theoretical foundations of MOPs and the MOACO algorithm, various MOACO variants documented in existing literature will be reviewed, and the specific application domains where MOACO has been implemented will be summarized. The critical discussion of the MOACO advantages and limitations is analyzed to provide better insight into the main research gaps in this domain. Finally, the conclusion and some possible future research directions of MOACO are also given in this work.\u0000","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"89 2 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantum Computational Intelligence Techniques: A Scientometric Mapping 量子计算智能技术：科学计量学图谱

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-07 DOI: 10.1007/s11831-024-10183-7

Mini Arora, Kapil Gupta

{"title":"Quantum Computational Intelligence Techniques: A Scientometric Mapping","authors":"Mini Arora, Kapil Gupta","doi":"10.1007/s11831-024-10183-7","DOIUrl":"https://doi.org/10.1007/s11831-024-10183-7","url":null,"abstract":"Computational intelligence has previously demonstrated its existence beyond the limitations of binary variables and Turing Machines. Using quantum concepts, Deutsch (1985) and Grover (1996) provide massive parallelism and searching techniques, vastly expanding the computational capacity of soft computing. This paper aims to analyze articles that consider both computational intelligence and quantum computing, referred to here as the quantum computational intelligence (QCI) category, to solve non-deterministic problems efficiently. The category includes 3067 research papers published from 2014 to 2023 that are indexed in high-quality databases like SCI and SCOPUS. This study examines QCI publishing patterns utilizing scientometric analysis employing co-occurrence, co-citation, and bibliographic coupling methodologies. Additionally, it provides insights into the citation patterns of publications, affiliations, and authors. China, USA, and India published more than half (53%) of the articles. The primary emphasis of application fields throughout this decade includes ‘Ground State Preparation’ and ‘Financial Forecasting’ among others. The pertinent keywords that have lately been studied are quantum particle swarm optimization (2022), optimization (2021), quantum circuits (2020), and deep learning (2019). Five quantum-based computation techniques were identified using a mix of critical review and cluster analysis: quantum machine learning, quantum neural networks, quantum particle swarm optimization, quantum variational Monte Carlo, and quantum-inspired evolutionary algorithms. The primary objective of this study is to address key queries that could contribute to future research in this field.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"145 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unveiling Alzheimer’s Disease Early: A Comprehensive Review of Machine Learning and Imaging Techniques 早期揭示阿尔茨海默病：机器学习和成像技术综述

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-06 DOI: 10.1007/s11831-024-10179-3

Wided Hechkel, Abdelhamid Helali

{"title":"Unveiling Alzheimer’s Disease Early: A Comprehensive Review of Machine Learning and Imaging Techniques","authors":"Wided Hechkel, Abdelhamid Helali","doi":"10.1007/s11831-024-10179-3","DOIUrl":"https://doi.org/10.1007/s11831-024-10179-3","url":null,"abstract":"Alzheimer’s disease (AD) represents a growing global health concern, emphasizing the urgent need for early detection and intervention strategies. This review article aims to provide a comprehensive analysis of the pivotal role that machine learning (ML) and advanced imaging techniques play in the early identification of AD. The study delves into an extensive array of methodologies, encompassing visual biomarkers, datasets, imaging modalities, and evaluation metrics essential for AD detection. The investigation encompasses diverse ML techniques, starting with pre-processing steps and extending to various data types, feature extractor models, and both conventional and deep learning algorithms. Highlighting the significance of Convolutional Neural Networks, Autoencoders, and Transfer Learning, the review assesses their efficacy in AD diagnosis. The findings underscore the intricate challenges and opportunities within the realm of AD detection. Notably, the integration of ML and imaging methods yields promising results in distinguishing AD patterns from healthy brain states. Robust models and algorithms demonstrated notable accuracy, sensitivity, and specificity when confronted with diverse datasets, thus paving the way for early AD identification. In conclusion, this review advocates for the pivotal role of ML and advanced imaging techniques in revolutionizing AD diagnosis. The amalgamation of these approaches holds immense potential for unveiling AD at its nascent stages, enabling timely therapeutic interventions and personalized patient care. Ultimately, this synthesis of biomedical research signifies a transformative leap towards addressing the pressing global issue of Alzheimer’s disease.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"5 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preserving Artistic Heritage: A Comprehensive Review of Virtual Restoration Methods for Damaged Artworks 保护艺术遗产：全面评述受损艺术品的虚拟修复方法

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-05 DOI: 10.1007/s11831-024-10175-7

Praveen Kumar, Varun Gupta

{"title":"Preserving Artistic Heritage: A Comprehensive Review of Virtual Restoration Methods for Damaged Artworks","authors":"Praveen Kumar, Varun Gupta","doi":"10.1007/s11831-024-10175-7","DOIUrl":"https://doi.org/10.1007/s11831-024-10175-7","url":null,"abstract":"Restoration of damaged artwork is an important task to preserve the culture and history of humankind. Restoration of damaged artwork is a delicate, complex, and irreversible process that requires preserving the artist’s style and semantics while removing the damages from the artwork. Digital restoration of artworks can guide artists in physically restoring artworks. This paper groups the virtual artwork restoration methods into various categories: image processing, machine learning, encoder-decoder neural networks, and generative adversarial network-based methods. This paper discusses and analyses different restoration methods’ underlying merits and demerits. The category-wise review of various artwork restoration methods reveals that the generative adversarial network-based methods have attracted the attention of researchers in recent years for restoring damaged artworks. This paper describes datasets used for training and testing of artwork restoration methods and discusses various metrics used for performance evaluation of the artwork restoration methods. This paper compares the restoration results of various methods quantitatively using performance evaluation metrics and qualitatively using visual inspection of the results. Further, the paper also identifies research gaps, challenges, and future directions for research in this field. The proposed review aims to provide researchers with an important reference for working in the artwork restoration field.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"404 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evolution of Piled Raft Foundation at Static Loading Condition and Application of Numerical Modelling: A State-of-the-Art Review 静载荷条件下桩筏基础的演变及数值建模的应用：最新技术综述

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-04 DOI: 10.1007/s11831-024-10172-w

Plaban Deb, Sujit Kumar Pal

{"title":"Evolution of Piled Raft Foundation at Static Loading Condition and Application of Numerical Modelling: A State-of-the-Art Review","authors":"Plaban Deb, Sujit Kumar Pal","doi":"10.1007/s11831-024-10172-w","DOIUrl":"https://doi.org/10.1007/s11831-024-10172-w","url":null,"abstract":"Piled raft foundation is a sustainable foundation approach in the current era due to the development of immense infrastructure. Initially, this foundation was primarily used for the construction of high-rise buildings in weaker soil bases, however, the application of piled raft systems is now extending to offshore and marine structures. This paper mainly concentrates on the review of available literature in the domain of the piled raft foundation and presents a critical review of the evolution of the piled raft from the past to till date. This state-of-the-art review starts from the early-age research and analytical works on the piled raft foundation. Various approaches suggested by several researchers are described here. The review also contains the experimental research conducted on piled rafts including the numerical analysis carried out on the existing case studies. The applications of different numerical software for the modelling of piled rafts are also described elaborately and the research related to the parametric analysis is accumulated together. The load sharing nature, interaction behaviour, and the influence of the loading system are reviewed separately depending upon the contribution of the research papers to the particular domain. There exist several design processes and selection criteria for the piled raft foundation and this is mainly due to the inadequate perception regarding the nature of the piled raft foundation during its overall applications. This literature review would be helpful for other researchers to acquire a clear idea of the behaviour of piled rafts and also would be useful to identify the future prospects of the piled raft foundation.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"68 1 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Systematic Survey on Segmentation Algorithms for Musculoskeletal Tissues in Ultrasound Imaging 关于超声成像中肌肉骨骼组织分割算法的系统调查

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-09-03 DOI: 10.1007/s11831-024-10171-x

Ananth Hari Ramakrishnan, Muthaiah Rajappa, Kannan Kirthivasan, Nachiappan Chockalingam, Panagiotis E. Chatzistergos, Rengarajan Amirtharajan

{"title":"A Systematic Survey on Segmentation Algorithms for Musculoskeletal Tissues in Ultrasound Imaging","authors":"Ananth Hari Ramakrishnan, Muthaiah Rajappa, Kannan Kirthivasan, Nachiappan Chockalingam, Panagiotis E. Chatzistergos, Rengarajan Amirtharajan","doi":"10.1007/s11831-024-10171-x","DOIUrl":"https://doi.org/10.1007/s11831-024-10171-x","url":null,"abstract":"Ultrasound imaging is widely used for the clinical assessment and study of musculoskeletal tissues because of its capacity for real-time imaging, low cost, high availability and portability. Objectively identifying and segmenting these tissues in ultrasound images can enhance disease diagnosis and biomechanical research. Manual segmentation is tedious, time-consuming and examiner-dependent. At the same time, ultrasound images suffer from poor image quality and low contrast between different regions in the image, making visual interpretation difficult. Hence, there is a need for reliable algorithms for computerised segmentation. This paper reviews the techniques developed for automated and semi-automated segmentation of vital musculoskeletal tissues (i.e. tendon, ligament, bone, muscle, plantar fascia and cartilage) from ultrasound images. This paper comprehensively explains each methodology and discusses distinguishing features, advantages and limitations to help the reader decide the most appropriate method on an application-specific basis.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"174 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Application in Prediction of Scour Around Bridge Piers: A Comprehensive Review 机器学习在桥墩周围冲刷预测中的应用：综合评述

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-08-28 DOI: 10.1007/s11831-024-10167-7

Farooque Rahman, Rutuja Chavan

{"title":"Machine Learning Application in Prediction of Scour Around Bridge Piers: A Comprehensive Review","authors":"Farooque Rahman, Rutuja Chavan","doi":"10.1007/s11831-024-10167-7","DOIUrl":"https://doi.org/10.1007/s11831-024-10167-7","url":null,"abstract":"Scour is one of the most difficult challenges faced by hydraulic engineers, which refers to the erosion of sediments that surrounds hydraulic structures. In the past, scour prediction has generally relied on physical models as well as empirical formulae. However, these methods may not satisfactorily account for the complex nature of scour processes. Hence, this paper aims to provide a concise overview of the latest advancements in the field of scour prediction, particularly focusing on the use of machine learning (ML) techniques. The review begins by examining the basic ideas and methodologies of various machine learning algorithms which are commonly employed, it then looks into the key factors that affect scour processes, including flow velocity, sediment characteristics, and bed morphology. The paper provides an in-depth assessment of the advantages and drawbacks of current machine learning models used for estimating scour, taking into account various issues such as the availability of data, models understandability, and their capacity to adapt in changing environmental conditions. This study will be a helpful resource for researchers, practitioners, and decision-makers in the field of hydraulic engineering. It provides insights into the evolving field of ML applications for predicting scour and sets the stage for the advancement of more precise and versatile scour prediction models.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"7 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Intelligence Applications in Composites: A Survey 人工智能在复合材料中的应用：调查

IF 9.7 2区工程技术

Archives of Computational Methods in Engineering Pub Date : 2024-08-27 DOI: 10.1007/s11831-024-10169-5

Ercüment Öztürk, Ayfer Dönmez Çavdar, Tuğrul Çavdar

{"title":"Artificial Intelligence Applications in Composites: A Survey","authors":"Ercüment Öztürk, Ayfer Dönmez Çavdar, Tuğrul Çavdar","doi":"10.1007/s11831-024-10169-5","DOIUrl":"https://doi.org/10.1007/s11831-024-10169-5","url":null,"abstract":"It is known that raw material resources have reached the point of depletion. Therefore, the search for alternative sources is becoming more and more common. The only product that can be considered as an alternative to raw material sources is composites. With the increase in its use in the industrial fields, studies in relation to increasing the quality of composites and reducing the production cost have recently gained attention. Experimental studies based on personal experience have now left their place to Information Technologies. Because IT is a good approach that can provide a solution to the improvement of low quality, long timeframes, and high cost in the experimental studies process. In this context, Artificial Intelligence technologies have the potential to provide better solutions and results. In this survey, a literature review on composites using AI technology was conducted. We have mainly focused on the foundations of the AI technology and its advantages in the field of composites. Consequently, it has been seen that the production of composites via IT approaches increases the quality, reduces the production costs, and abridges the experimental production process.","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"14 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0