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arXiv 2020年

作者： Zhu, Tuanfei Luo, Cheng Li, Jing Ren, Siqi Zhang, Zhihong College of Computer Engineering and Applied Mathematics Changsha University Changsha410000 China School of Information Technology and Management Hunan University of Finance and Economics Changsha410205 China School of Information Engineering Jiangxi Vocational Technical College of Industry and Trade Nanchang330038 China School of Computer and Information Engineering Zhejiang Gongshang University Hangzhou310000 China

Many important real-world applications involve time-series data with skewed distribution. Compared to conventional imbalance learning problems, the classification of imbalanced time-series data is more challenging due to high dimensionality and high inter-variable correlation. This paper proposes a structure preserving Oversampling method to combat the High-dimensional Imbalanced Time-series classification (OHIT). OHIT first leverages a density-ratio based shared nearest neighbor clustering algorithm to capture the modes of minority class in high-dimensional space. It then for each mode applies the shrinkage technique of large-dimensional covariance matrix to obtain accurate and reliable covariance structure. Finally, OHIT generates the structure-preserving synthetic samples based on multivariate Gaussian distribution by using the estimated covariance matrices. Experimental results on several publicly available time-series datasets (including unimodal and multimodal) demonstrate the superiority of OHIT against the state-of-the-art oversampling algorithms in terms of F1, G-mean, and AUC. Copyright © 2020, The Authors. All rights reserved.

关键词： Covariance matrix

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Analytical study on impact strength of steel fibre reinforced concrete

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Journal of Physics: Conference Series 2021年第1期1913卷

作者： Kaplana G Lokhande Satyajit S Uparkar Vikrant S Vairagde AshiwiniA Kulkarni Department of Applied Mathematics Priyadarshini College of Engineering Nagpur India Department of Computer Application Shri Ramdeobaba College of Engineering and Management Nagpur India Department of Civil Engineering Priyadarshini College of Engineering Nagpur India

In Recent years, there has been an increasing tendency to build resilience to the impact of civilian and military infrastructure due to the increasing number of attacks or calamities. An alternative solution is to improve the impact resistance of such structures is to incorporate different types and dosages of fibres into the concrete that can greatly reduce the damage of concrete structures due to the impact load. This research work focuses on the experimental setup based on Drop Weight Test-Ac1 544. The objective is to build a model for impact energy using variation in plain concrete and fibre reinforced concrete. Furthermore, this research work investigates and describes the impact resistance of fibre reinforced concrete to calculate the reliability of model. Lastly this analytical study is based on testing an experimental model using various mathematical and statistical methods.

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Erratum to:Recent Advances of Chimp Optimization Algorithm:Variants and Applications

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Journal of Bionic engineering 2024年第3期21卷 1618-1618页

作者： Mohammad Sh.Daoud Mohammad Shehab Laith Abualigah Mohammad Alshinwan Mohamed Abd Elaziz Mohd Khaled Yousef Shambour Diego Oliva Mohammad A.Alia Raed Abu Zitar College of Engineering Al Ain University112612 Abu DhabiUnited Arab Emirates College of Computer Sciences and Informatics Amman Arab UniversityAmman 11953Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq 25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied Science Research Center Applied Science Private UniversityAmman 11931Jordan School of Computer Sciences Universiti Sains Malaysia11800 Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio′n Basada en la Informacio′n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber Security Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates School of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Erratum to:J Bionic Eng https://***/10.1007/*** this article the statement in the Funding information section was incorrectly given as‘22UQU4361183DSR03’and should have read‘23UQU4361183DSR03’.

关键词： statement section correctly

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Analysis of fuzzy inventory model with sustainable transportation

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AIP Conference Proceedings 2023年第1期2782卷

作者： Pushpendra Kumar Vikasdeep Yadav Purvi J. Naik A. K. Malik Satish Kumar Alaria Department of Mathematics Seth. G. B. Podar College Nawalgarh Jhunjhunu Rajasthan India Bhagwant University Ajmer Rajasthan India Department of Mathematics Science & Humanities UPL University of Sustainable Technology Bharuch Gujarat India Department of Applied Science & Humanities B K Birla Institute of Engineering & Technology Pilani Rajasthan India Department of Computer Science & Engineering Arya Institute of Engineering & Technology Jaipur Rajasthan India

In recent years, the concept of sustainability and its development has gained a lot of popularity among transportation and inventory management systems. One of the most important aspects of any inventory control system is providing adequate storage facilities for an item. This study introduces the Fuzzy-Based Signed-distance Method (F-BSDM), which is an excellent tool for assessing the long-term viability of various inventory regimes. The problem is modelled as an optimization programming problem that is solved using optimization techniques, as well as a fuzzy model that is solved using the Signed distance approach. In research activity, when some parameters are difficult to assign values to or are seldom ever genuine, the reliability of any technique is a crucial aspect in the inventory system.

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A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problem

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2020年第1期21卷 9253-9290页

作者： Peipei Tang Chengjing Wang Defeng Sun Kim-Chuan Toh School of Computer and Computing Science Zhejiang University City College Hangzhou China School of Mathematics and National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu China Department of Applied Mathematics The Hong Kong Polytechnic University Hung Hom Hong Kong Department of Mathematics and Institute of Operations Research and Analytics National University of Singapore Singapore

In this paper, we consider high-dimensional nonconvex square-root-loss regression problems and introduce a proximal majorization-minimization (PMM) algorithm for solving these problems. Our key idea for making the proposed PMM to be efficient is to develop a sparse semismooth Newton method to solve the corresponding subproblems. By using the Kurdyka-Łojasiewicz property exhibited in the underlining problems, we prove that the PMM algorithm converges to a d-stationary point. We also analyze the oracle property of the initial subproblem used in our algorithm. Extensive numerical experiments are presented to demonstrate the high efficiency of the proposed PMM algorithm.

关键词： nonconvex square-root regression problems proximal majorization-minimization semismooth Newton method

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GFSOM: Genetic Feature Selection for Ontology Matching 12th

GFSOM: Genetic Feature Selection for Ontology Matching

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12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018

作者： Belhadi, Hiba Akli-Astouati, Karima Djenouri, Youcef Lin, Jerry Chun-Wei Wu, Jimmy Ming-Tai Algiers Bab Ezzouar Algeria Trondheim Norway Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway College of Computer Science and Engineering Shandong University of Technology Shandong China

ISBN: (纸本)9789811358401

This paper studies the ontology matching problem and proposes a genetic feature selection approach for ontology matching (GFSOM), which exploits the feature selection using the genetic approach to select the most appropriate properties for the matching process. Three strategies are further proposed to improve the performance of the designed approach. The genetic algorithm is first performed to select the most relevant properties, and the matching process is then applied to the selected properties instead of exploring all properties of the given ontology. To demonstrate the usefulness and accuracy of the GFSOM framework, several experiments on DBpedia ontology database are conducted. The results show that the ontology matching process benefits from the feature selection and the genetic algorithm, where GFSOM outperforms the state-of-the-art ontology matching approaches in terms of both the execution time and quality of the matching process. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Semantic Web

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Linguistic Pythagorean fuzzy Aczel–Alsina aggregation operators and their application in multi-attribute group decision-making: An approach for smart city development

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engineering Applications of Artificial Intelligence 2025年 156卷

作者： Shahid Hussain Gurmani Zunaira Rasool Rifaqat Ali Shehr Bano Huayou Chen Yuming Feng Rana Muhammad Zulqarnain School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Agriculture Engineering and Food Science Shandong University of Technology Zibo China Department of Botany College of Life Sciences Government College University Allama Iqbal Road Faisalabad 38000 Pakistan Department of Mathematics Applied College in Mohayil Asir King Khalid University Abha Saudi Arabia Institute of Zoology Bahauddin Zakariya University Multan Pakistan School of Big Data and Statistics Anhui University Hefei 230601 Anhui China Institute of Intelligent Information Processing South China Business College of Guangdong University of Foreign Studies Guangzhou 510545 Guangdong China Department of Mathematics Saveetha School of Engineering SIMATS Thandalam Chennai 602105 Tamilnadu India

This paper aims to present a new multi-attribute group decision-making (MAGDM) approach for solving problems in an uncertain and complex environment. In any MAGDM problem, the key challenge is how to quantify and aggregate the objective uncertainty information contained in the data. To answer this, in this paper, we utilize the idea of linguistic Pythagorean fuzzy set (LP y FS) to describe the information in terms of linguistic membership degree (LMD) and linguistic non-membership degree (LNMD). We first present some new operations of LP y FS, including Aczel–Alsina (AA) sum, AA product, and AA scalar multiplication. At that point, we develop various LP y F aggregation operators which are based on these defined operations, including the LP y F Aczel–Alsina weighted averaging (LP y FAAWA) operator, the LP y F Aczel–Alsina ordered weighted averaging (LP y FAAOWA) operator, LP y F Aczel–Alsina weighted geometric (LP y FAAWG) operator and LP y F Aczel–Alsina ordered weighted geometric (LP y FAAOWG) operator. We configure these operators with different characteristics. It can be seen that the proposed operators have commutativity, monotonicity, boundary, and idempotency properties. Then, we design a new technique dependent on these operators to solve MAGDM problems. The applicability of the established approach is demonstrated through a case study related to smart city development. The result demonstrates the new technique's feasibility and applicability. In the end, sensitivity analysis and a systematic comparison between the prevailing and suggested techniques are given.

关键词： Aggregation operators Alczel Alsina operations Linguistic Pythagorean fuzzy Alczel Alsina operators Linguistic Pythagorean fuzzy set Multi-attribute group decision-making

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A multi-block grids load balancing algorithm with improved block partitioning strategy 21

A multi-block grids load balancing algorithm with improved b...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Xiong, Hantao Li, Kenli Liu, Xu Li, Keqin College of Information Science and Engineering Hunan University Changsha China Institute of Applied Physics and Computational Mathematics Beijing China Department of Computer Science State University of New York New York United States

ISBN: (纸本)9781728120584

In recent years, high performance computing is developing at a very fast speed, with more processors and larger communication bandwidth, bringing more powerful computing capability and a faster communication speed. The numerical simulation in scientific and engineering computing is a vital kind of application in the field of high performance computing. The load balancing efficiency and communication overheads mainly determine the simulation quality and speed. In order to obtain better simulation quality and speed up the execution of simulation programs, all the processors should be as load-balanced as possible, which means that the multi-block grids are mapped to processors as evenly as possible in terms of computational load, and meanwhile, with the minimum communication overheads among all the processors. To address the above problem, we propose a new structured multi-block grids load balancing algorithm, which combines the recursive edge bisection (REB) algorithm and the modified rectangular partitioning method through new optimal computational load interval and computational load lower bound. Firstly, our algorithm processes the original multi-block grids. Improved optimal computational load interval and computational load lower bound are adopted to evaluate a certain block and decide whether the block needs to be partitioned by strategies such as the modified rectangular partitioning and the recursive edge bisection. Secondly, our algorithm maps the processed multi-block grids into processors. Experiments show that our new structured multi-block grids load balancing algorithm can achieve both better load balancing efficiency and relatively lower communication overheads among all the processors. © 2019 IEEE.

关键词： Efficiency

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Mathematical modelling and analysis of COVID-19 and tuberculosis transmission dynamics

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Informatics in Medicine Unlocked 2023年 38卷 101235页

作者： Singh, Ram Rehman, Attiq ul Ahmed, Tanveer Ahmad, Khalil Mahajan, Shubham Pandit, Amit Kant Abualigah, Laith Gandomi, Amir H. Department of Mathematical Sciences BGSB University Rajouri 185234 India Department of Mathematics Al-Falah University Faridabad India Ajeenkya D Y Patil University Pune Maharashtra 412105 India University Center for Research & Development (UCRD) Chandigarh University Mohali India School of Electronic and Communication Shri Mata Vaishno Devi University Katra 182320 India Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al al-Bayt University Mafraq 25113 Jordan College of Engineering Yuan Ze University Taiwan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan Faculty of Information Technology Middle East University Amman 11831 Jordan Applied science research center Applied science private university Amman 11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang 11800 Malaysia Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW 2007 Australia University Research and Innovation Center (EKIK) Óbuda University Budapest 1034 Hungary

In this paper, a mathematical model for assessing the impact of COVID-19 on tuberculosis disease is proposed and analysed. There are pieces of evidence that patients with Tuberculosis (TB) have more chances of developing the SARS-CoV-2 infection. The mathematical model is qualitatively and quantitatively analysed by using the theory of stability analysis. The dynamic system shows endemic equilibrium point which is stable when R₀<1 and unstable when R₀>1. The global stability of the endemic point is analysed by constructing the Lyapunov function. The dynamic stability also exhibits bifurcation behaviour. The optimal control theory is used to find an optimal solution to the problem in the mathematical model. The sensitivity analysis is performed to clarify the effective parameters which affect the reproduction number the most. Numerical simulation is carried out to assess the effect of various biological parameters in the dynamic of both tuberculosis and COVID-19 classes. Our simulation results show that the COVID-19 and TB infections can be mitigated by controlling the transmission rate γ. © 2023 The Author(s)

关键词： Bifurcation COVID-19 Modelling Optimal solution Sensitivity analysis

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Corrigendum to “Numerical investigation for MHD Prandtl nanofluid transportation due to a moving wedge: Keller box approach” [International Communications in Heat and Mass Transfer 135 (2022) 106141]

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International Communications in Heat and Mass Transfer 2023年 146卷

作者： Danial Habib Nadeem Salamat Sajjad Hussain Sohaib Abdal Bagh Ali Department of Mathematics Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan Department of Mathematics Government College University Faisalabad Layyah Campus Pakistan School of Aerospace and Mechanical Engineering Nanyang Technological University Singapore School of Mathematics Northwest University No.229 North Taibai Avenue Xi'an 710049 China Department of Applied Mathematics Northwestern Polytechnical University 127 West Youyi Road Xian 710072 China Faculty of Computer Science and Information Technology Superior University Lahore 54000 Pakistan

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