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12th International Conference on Soft computing for Problem Solving, SocProS 2023

作者： Joshi, Shubham Panwar, Ankita Pant, Millie Deep, Kusum Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India Department of Mathematics Indian Institute of Technology Uttarakhand Roorkee247667 India Mehta Family School for Data Science and Artificial Intelligence Indian Institute of Technology Uttarakhand Roorkee247667 India

ISBN: (纸本)9789819731794

In this study, an analysis has been performed to assess the performance of 28 states and 8 union territories (UTs) of India against COVID-19 during the years 2020 and 2021. The study is done in three phases;first of all, the analysis has been done through Exploratory Data Analysis (EDA), to get general information about the data;in the second phase, the super-efficiency-data envelopment analysis (SE-DEA) model has been applied to evaluate the performance of states and UTs, and to segregate them into two classes: efficient and inefficient. Finally, in the third phase, an attempt is made to establish a link between the DEA and 5 supervised machine learning techniques viz. Logistic regression (LR), K-nearest neighbours (KNN), Support vector machine (SVM), Naïve Bayes (NB) classifier, and Decision tree (DT) for analysis of the results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： COVID-19

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Mathematical model of COVID-19 dynamics in the presence of multiple controls

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Quality and Quantity 2024年第1期59卷 261-290页

作者： Akanni, J.O. Fatmawati Ajao, S. Asamoah, J.K.K. Abimbade, S.F. Department of Mathematical and Computing Sciences Koladaisi University Oyo State Ibadan Nigeria Department of Mathematics Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia Department of Mathematics and Computer Science Elizade University Ondo State Ilara-Mokin Nigeria Department of Mathematics Saveetha School of Engineering SIMATS Chennai India Department of Mathematics Kwame Nkrumah University of Science and Technology Kumasi Ghana Department of Pure and Applied Mathematics Ladoke Akintola University of Technology Oyo State Ogbomoso Nigeria

The coronavirus disease 19 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), is an infectious disease constituting the most significant challenge to human and socio-economic development across the globe. Many studies have been conducted to gain more knowledge on the dynamic spread of SARS-COV-2 in the community of people. In this study, a new mathematical model made up of a system of non-linear ODEs is designed and meticulously analyzed to understand the dynamics of transmission of COVID-19. Specific necessary properties exhibited by the COVID-19 model are examined through the theory of non-negativity and boundedness of solutions. The threshold parameter measuring the invasion potential of COVID-19 in the population is worked out by employing the Next Generation Matrix approach. The model is shown to have two endemic equilibria whenever basic reproduction number R₀<1. The analysis of the endemic equilibrium stability is explored using a suitably constructed Lyapunov function. It is shown that the COVID-19 model is globally asymptotically stable whenever the associated basic reproduction number is beyond unity. The Latin Hypercube Sampling or Partial Rank Correlation Coefficient is utilized to examine how parameter changes affect the COVID-19 spread in the population. Furthermore, the study considers six optimal control interventions to flatten the curve of the coronavirus pandemic in society. Numerical experiments of the COVID-19 model are executed in MatLab to corroborate the qualitative analysis of the model. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： 49J15 cost-effectiveness analysis COVID-19 Dynamical system LHS/PRCC Mathematical modelling Optimal control analysis Sensitivity analysis

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Application of Deep Learning Technologies in Serious Games 5

Application of Deep Learning Technologies in Serious Games

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5th International Conference on Problems of Cybernetics and Informatics, PCI 2023

作者： Mammadli, Anar Ismayilov, Elviz A. Azerbaijan State Oil and Industry University High Performance Computing Center Baku Azerbaijan Azerbaijan State Oil and Industry University General and Applied Mathematics Department Baku Azerbaijan

ISBN: (纸本)9798350319064

Text classification is one of the important and classic problems. A number of studies have been conducted in this area. As in any field, classification plays an important role in serious games. However, a limited amount of work has been done on Graph Neural Networks. This work deals with the application of Graph Neural Network in serious games. We build a graph network consisting of text and their connections and implement the classification process by applying the Text Graph Neural Network. Our results suggest that GNNs may significantly improve text classification performance in serious games by capturing semantic and syntactic relationships between text units. This gives players a more personalized and engaging gaming experience, and ultimately better learning outcomes. © 2023 IEEE.

关键词： Serious games

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Characterizing Generalized Windmill Graphs in terms of Complexity Measures via Eccentricity Dependent Topological Indices 3

Characterizing Generalized Windmill Graphs in terms of Compl...

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3rd International Symposium on Computer Technology and Information Science, ISCTIS 2023

作者： Wang, Wenhu Vladimir, Mariano Abisado, Mideth Mujahid, Nabeel School of Software Pingdingshan University China College of Computing and Information Technologies National University Philippines Bahauddin Zakariya University Cenrre for Advanced Studies in Pure and Applied Mathematics Pakistan

ISBN: (纸本)9798350325386

Windmill graphs have a crucial role in the field of computer science, mathematics, electrical engineering and physics. Generalized windmill graphs are a generalization of the classic windmill graphs with applications in network communication, optimization, wireless sensor networks, ad-hoc networks, and distributed computing systems. By studying the entropy and complexity measures of generalized windmill graphs, we can gain insights into the behavior of these systems and optimize their performance. In this paper, firstly, we compute the Eccentricity dependent indices by developing suitable partitions of the vertex and the edge set of the generalized windmill graphs. Moreover, to present applications, we define different information functionals and obtain analytical formulae for entropies of generalized windmill graphs. These entropy measures assist us to understand the complexity measures of these graphs. As a specific application, we obtain numeric tables from our proved results which show how the studied model presents the comparison between the complexities of generalized windmill graphs of type I, type II and type III. © 2023 IEEE.

关键词： Graphic methods

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Learning Not to Regret 38

Learning Not to Regret

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Sychrovský, David Šustr, Michal Davoodi, Elnaz Bowling, Michael Lanctot, Marc Schmid, Martin Department of Applied Mathematics Charles University Czech Republic Artificial Intelligence Center Czech Technical University Czech Republic Google DeepMind United Kingdom Department of Computing Science University of Alberta Canada EquiLibre Technologies

ISBN: (纸本)1577358872

The literature on game-theoretic equilibrium finding predominantly focuses on single games or their repeated play. Nevertheless, numerous real-world scenarios feature playing a game sampled from a distribution of similar, but not identical games, such as playing poker with different public cards or trading correlated assets on the stock market. As these similar games feature similar equilibra, we investigate a way to accelerate equilibrium finding on such a distribution. We present a novel "learning not to regret" framework, enabling us to meta-learn a regret minimizer tailored to a specific distribution. Our key contribution, Neural Predictive Regret Matching, is uniquely meta-learned to converge rapidly for the chosen distribution of games, while having regret minimization guarantees on any game. We validated our algorithms' faster convergence on a distribution of river poker games. Our experiments show that the meta-learned algorithms outpace their non-meta-learned counterparts, achieving more than tenfold improvements. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Game theory

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EXISTENCE OF WEAK SOLUTIONS FOR OBSTACLE PROBLEMS WITH VARIABLE GROWTH IN ORLICZ-SOBOLEV SPACES

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Journal of Mathematical Sciences (United States) 2024年第2期289卷 155-167页

作者： Allalou, Mouad Ait Temghart, Said Raji, Abderahmane Applied Mathematics and Scientific Computing Laboratory Faculty of Science and Technics Sultan Moulay Slimane University BP 523 Beni Mellal 23000 Morocco National Higher School for Artificial Intelligence and Data Sciences Ibn Zohr University Taroudant 83000 Morocco

This article delves into the exploration of weak solutions’ existence within the context of obstacle problems associated with the following inequality: ∫ΩV(z,w,Dw):D(v-w)dz≥g,v-w, where v lies in a convex set FO,B... 详细信息

This article delves into the exploration of weak solutions’ existence within the context of obstacle problems associated with the following inequality: ∫_ΩV(z,w,Dw):D(v-w)dz≥g,v-w, where v lies in a convex set F_O,B. The primary methodology employed in this investigation involves the utilization of You ng’s measure theory, complemented by a theorem originating from Kinderlehrer and Stampacchia, specifically tailored for reflexive Orlicz-Sobolev spaces. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： 28A33 35J88 46E30 46E35 Kinderlehrer and Stampacchia Obstacle problem Orlicz-Sobolev spaces Young’s measures

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Multi-Criteria Decision-Making for Energy Management in Smart Homes Using Hybridized Neuro-Fuzzy Approach

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Distributed Generation and Alternative Energy Journal 2024年第1期39卷 83-109页

作者： Anbazhagu, U.V. Koti, Manjula Sanjay Muthukumaran, V. Geetha, V. Munrathnam, Meram Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur TN Chennai India Department of MCA Dayananda Sagar Academy of Technology and Management Bangalore560082 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur Campus 603 203 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R.k.Valley Idupulapaya Andhra Pradesh Kadapa516330 India

The necessity for smart energy oversight solutions has arisen in response to the rising popularity of energy-efficient home automation and other energy-saving technologies. Optimizing smart home energy use using multi-criteria decision-making (MCDM) is a proven methodology. However, the procedure for making decisions and MCDM’s capacity to handle various criteria are typically limiting factors. Hybrid methods, which integrate multiple decision-making approaches like Fuzzy Logic (FL) and Modular Neural Networks (MNN), could potentially be able to circumvent these restrictions and boost energy management systems’ efficacy and precision. This investigation presents a hybrid Neuro-Fuzzy (H-NF) method for MCDM in regulating energy for smart homes by combining FL with an MNN. The suggested approach would optimize energy use in smart homes by considering several parameters, notably cost, ease of use, and environmental effects. In addition, this study aims to examine how the H-NF model fares in comparison to other methods of making important decisions in terms of several performance metrics. The suggested hybridized approach has the potential to deliver more precise and effective decision-making processes for energy management in smart homes, allowing users to optimize their energy consumption while preserving comfort and lowering environmental impact. © 2024 Taylor and Francis Inc.. All rights reserved.

关键词： Decision making

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EXISTENCE OF SOLUTIONS FOR THE FRACTIONAL KIRCHHOFF PARABOLIC EQUATION WITH LOGARITHMIC NONLINEARITY

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Journal of Mathematical Sciences (United States) 2025年 1-10页

作者： Talibi, Ihya El Boukari, Brahim El Ghordaf, Jalila Applied Mathematics and Scientific Computing Laboratory Sultan Moulay Slimane University P.O. Box 523 Beni Mellal 23000 Morocco

In this work, we study the local existence of weak solutions for a Kirchhoff-type problem involving the fractional p-Laplacian. Under appropriate assumptions, we obtain the existence of weak solutions by using the Galerkin method combined with the Sobolev inequalities. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Existence Fractional p-Laplacian Galerkin method Kirchhoff Weak solution

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PATH PLANNING FOR AUTONOMOUS VEHICLES WITH MINIMAL COLLISION SEVERITY

arXiv

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arXiv 2024年

作者： Wang, Qiannan Gerdts, Matthias Institute of Applied Mathematics and Scientific Computing Universität der Bundeswehr München Germany

This paper proposes a path planning algorithm for autonomous vehicles, evaluating collision severity with respect to both static and dynamic obstacles. A collision severity map is generated from ratings, quantifying the severity of collisions. A two-level optimal control problem is designed. At the first level, the objective is to identify paths with the lowest collision severity. Subsequently, at the second level, among the paths with lowest collision severity, the one requiring the minimum steering effort is determined. Finally, numerical simulations were conducted using the optimal control software OCPID-DAE1. The study focuses on scenarios where collisions are unavoidable. Results demonstrate the effectiveness and significance of this approach in finding a path with minimum collision severity for autonomous vehicles. Furthermore, this paper illustrates how the ratings for collision severity influence the behaviour of the automated *** Codes 49M99 © 2024, CC BY-NC-ND.

关键词： Autonomous vehicles

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A Polynomial Time Algorithm for Steiner Tree when Terminals Avoid a Rooted K4-Minor

arXiv

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arXiv 2024年

作者： Groenland, Carla Nederlof, Jesper Koana, Tomohiro Delft Institute of Applied Mathematics Netherlands Utrecht University Department of Information and Computing Sciences Netherlands

We study a special case of the Steiner Tree problem in which the input graph does not have a minor model of a complete graph on 4 vertices for which all branch sets contain a terminal. We show that this problem can be solved in O(n4) time, where n denotes the number of vertices in the input graph. This generalizes a seminal paper by Erickson et al. [Math. Oper. Res., 1987] that solves Steiner tree on planar graphs with all terminals on one face in polynomial time. Copyright © 2024, The Authors. All rights reserved.

关键词： Trees (mathematics)

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