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Enhancing Fraud Detection in Credit Card Transactions using Optimized Federated Learning Model

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第5期15卷 258-263页

作者： Salam, Mustafa Abdul El-Bably, Doaa L. Fouad, Khaled M. Elsayed, M. Salah Eldin Benha Univ Fac Comp & Artificial Intelligence Banha Egypt Prince Sattam Bin Abdulaziz Univ Dept Comp Engn & Informat Coll Engn Al Kharj 16273 Saudi Arabia New Mansoura Univ Fac Comp Sci & Engn Mansoura Egypt Higher Inst Comp & Informat Technol Cairo Egypt

In recent years, credit card transaction fraud has inflicted significant losses on both consumers and financial institutions. To address this critical issue, we propose an optimized framework for fraud detection. This study deals with non-identically independent distributions (IIDs) involving different numbers of clients. The proposed framework empowers banks to construct robust fraud detection models using their internal training data. Specifically, by optimizing the initial global model before to the federated learning phase, the suggested optimization technique accelerates convergence speed by reducing communication costs when moving forward with federal training. The optimization techniques using the three most recent metaheuristic Optimizers, namely: An improved gorilla troops optimizer (AGTO), Coati optimization Algorithm (CoatiOA), Coati optimization Algorithm (COA). Furthermore, credit card data is highly skewed, which makes it challenging to predict fraudulent transactions. The resampling strategy is used as a preprocessing step to improve the outcomes of unbalanced or skewed data. The performance of these algorithms is documented and compared. Computation time, accuracy, precision, recall, F-measure, loss, and computation time are used to assess the algorithms' performance. The experimental results show that AGTO and (CoatiOA) exhibit higher accuracy, precision, recall, and F1 scores compared to the baseline FL Model. Additionally, they achieve lower loss values.

关键词： Credit card fraud detection (CCFD) federated learning optimization algorithms identically independent distributions (IIDs) metaheuristic optimization techniques

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A Centralized Optimal Energy Management System for Microgrids

A Centralized Optimal Energy Management System for Microgrid...

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IEEE Power and Energy Society General Meeting

作者： Daniel E. Olivares Claudio A. Canizares Mehrdad Kazerani University of Waterloo

ISBN: (纸本)9781457710001

The issue of controlled and reliable integration of distributed energy resources into microgrids and large power grids has recently gained considerable attention. The microgrid concept, which basically corresponds to the coordinated operation of a cluster of loads, distributed generators and energy storage systems, is quite appealing due to its flexibility, controllability and energy management capabilities. In order to provide uninterruptible power supply to the loads, microgrids are expected to operate in both grid-connected and stand-alone modes, and economically meet the demand on an instantaneous basis. The problem of optimal management of the resources in a microgrid is being widely investigated and recent studies have proposed the application of both centralized and distributed control schemes by using multi-agent systems, heuristic methods and optimization algorithms. This paper elaborates on the conceptual design of a centralized energy management system (EMS) and its desirable attributes for a microgrid in stand-alone mode of operation. A number of test protocols are proposed to analyze the performance of the system, as well as the impacts of relevant parameters.

关键词： Microgrids Distributed generation Energy management systems Multi-stage optimization Energy management systems MICRO-GRID distributed power generation coordinated operation Uninterruptible power supply distributed energy resources operation mode Power grids management of resources LOAD correlation parameter stand-alone data recorder optimization algorithms

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Optimizing Nerve Cuff Stimulation of Targeted Regions Through Use of Genetic algorithms

Optimizing Nerve Cuff Stimulation of Targeted Regions Throug...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Natalie Brill Dustin Tyler Case Western Reserve University

ISBN: (纸本)9781424441211

A nerve cuff electrode is a viable technology for use in a neuroprostheses system to restore loss of function due to neurological injury. The Flat Interface Nerve Electrode (FINE) is a nerve cuff that gently reshapes the nerve to bring the axons closer to the stimulating contacts. The overall goal of this work is to optimize nerve cuff stimulation in upper extremity nerves. Recently, highly efficient and accurate linear models of neuronal activation have been developed in our lab. Using the fast calculations from the newly developed linear activation method, nerve stimulation parameters such as current pulse width and pulse amplitude at many electrode contacts can be explored by employing optimization algorithms. Finite element nerve models with high density electrodes were constructed based on upper extremity cadaveric nerve cross sections. An objective function was developed to target specific groups of nerve fascicles and minimize overlap amongst these groups. By changing the objective function and using a genetic search algorithm, stimulation parameters can be optimized for many contacts.

关键词： Nerve nerve cuff Genetic Algorithm (GA) Objective function linear models Electrodes pulse amplitude Cross section optimization algorithms CONTACT Upper Extremity Stimuli

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The multiple knapsack problem with compatible bipartite graphs

The multiple knapsack problem with compatible bipartite grap...

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12th International Symposium on Operations Research and its Applications in Engineering, Technology and Management (ISORA 2015)

作者： Jianping Li Weidong Li Hao Wang Yunnan University Kunming China

The multiple knapsack problem is to pack some items into given knapsacks, such that the sum of the knapsack profits is maximized. This paper is concerned with a variant of the multiple knapsack problem, called the multiple knapsack problem with compatible bipartite graph (MKPCBG), where two items can be packed into the same knapsack only if their corresponding vertices are adjacent in the given compatible bipartite graph. Under two different objectives, we prove that the MKPCBG problem is strongly NP-hard, design some 1/2-approximation algorithms, and design two optimal algorithms for the special case where all knapsacks have the same capacity.

关键词： Multiple knapsack problem approximation algorithm bipartite graph non-approximability optimal algorithm knapsack problems Bipartite graph optimization algorithms Approximation algorithms

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μAO-MPC: a Free Code Generation Tool for Embedded Real-Time Linear Model Predictive Control

μAO-MPC: a Free Code Generation Tool for Embedded Real-Time...

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American Control Conference

作者： Pablo Zometa Markus Kogel Rolf Findeisen Institute for Automation Engineering Otto-von-Guericke-University Magdeburg Germany

ISBN: (纸本)9781479901777

Implementing linear model predictive controllers in embedded systems with limited computational resources is still challenging. Recently, several code generation tools have been developed that produce highly efficient library-free optimization algorithms. We present a tool that focuses on controller performance and hardware with low computational resources. The underlying optimization algorithm has been explicitly developed for real-time embedded applications, and is based on an augmented Lagrangian method together with Nesterov's gradient method. The tool provides offline methods that allow the generation of online controllers that have low computational requirements and quickly reach good performance. We demonstrate the capabilities of the software, and the performance of the generated controllers with two examples.

关键词： Code generation optimization algorithms Lagrangian method linear models Controllers Embedded systems Predictive control Computer hardware real-time application program computer software

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Closed-Loop Optimal System Synthesis in the Mode Of “Special” Control of a Continuous Induction Heater

Closed-Loop Optimal System Synthesis in the Mode Of “Specia...

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International Conference on Complex Systems: Control and Modeling Problems (CSCMP)

作者： Aleksander Danilushkin Samara State Technical University Samara Russian Federation

ISBN: (纸本)9781728167015

The article deals with the problem of synthesizing the system of the optimal control of transient modes of a through-type induction heater. An algorithm to control the inductor power is obtained for the case of varying the performance of the technological complex. It is shown that the optimal algorithm for the transient mode has the form of a periodic decaying piecewise continuous function of time with discontinuities of the first kind. The number of intervals of continuity is infinite. It is noted that under conditions of random noise and a wide variety of process parameters, the synthesis of a closed-loop optimal system with temperature feedback seems to be the most appropriate. A specific feature of optimal control algorithms for non-stationary modes is the most using “special” control intervals. The conditions of absolute equality between the current value of the metal temperature at the exit from the heater and the given value are satisfied on “special” intervals of the trajectory. In this case, the temperature of the metal at the exit from the heater remains constant during the all transient modes. Therefore, the synthesis of closed-loop systems with feedback on the metal temperature at the exit from the heater is, in principle, impossible. At the same time, the metal temperature inside the heater varies according to certain regularity in accordance with the optimal algorithm. This established behavior allows us to synthesize a closed-loop system on the “special” interval of optimal control as a system with feedback on temperature at some “internal” point of the heater. Analyzing the nature of the metal temperature distribution along the length of the heater in a transient mode allows to determine the coordinate of the internal point at which the temperature changes with a maximum deviation from the steady-state value. This coordinate is used to set the feedback sensor. A relationship has been established between the temperature change at the control point and

关键词： optimization Operation Synthesis Phase trajectory Distributed system Heaters Distributed Systems control point transient model Optimal control trajectory Feedback synthesis EXITS induction heater temperature feedback Closed loop systems Piecewise Continuous Function temperature change optimization algorithms

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Success and Failure of Adaptation-Diffusion algorithms for Consensus in Multi-Agent Networks

Success and Failure of Adaptation-Diffusion Algorithms for C...

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IEEE Annual Conference on Decision and Control

作者： Gemma Morral Pascal Bianchi Gersende Fort LTCI Telecom Paris-Tech & CNRS 46 rue Barrault 75634 Paris Cedex 13 France

ISBN: (纸本)9781467360890

This paper investigates the problem of distributed stochastic approximation in multi-agent systems. The algorithm under study consists of two steps: a local stochastic approximation step and a gossip step which drives the network to a consensus. The gossip step uses row-stochastic matrices to weight network exchanges. We first prove the convergence of a distributed optimization algorithm, when the function to optimize may not be convex and the communication protocol is independent of the observations. In that case, we prove that the average estimate converges to a consensus;we also show that the set of limit points is not necessarily the set of the critical points of the function to optimize and is affected by the Perron eigenvector of the mean-matrix describing the communication protocol. Discussion about the success or failure of convergence to the minimizers of the function to optimize is also addressed. In a second part of the paper, we extend the convergence results to the more general context of distributed stochastic approximation.

关键词： Communication protocols Converge stochastic approximation NETWORKING AGENT optimization algorithms Gossip Set of points Convexity

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Multi-Agent Control for Centralized Air Conditioning Systems Serving Multi-Zone Buildings

Multi-Agent Control for Centralized Air Conditioning Systems...

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American Control Conference

作者： Jie Cai Donghun Kim Vamsi K. Putta James E. Braun Jianghai Hu School of Mechanical Engineering West Lafayette IN 47906 USA School of Electrical and Computer Engineering West Lafayette IN 47906 USA

ISBN: (纸本)9781479917730

Coordinating different components in a complex air conditioning system is challenging for centralized controls due to the large number of optimization variables. In this scenario, de-centralized controls are more appropriate alternatives. This study proposes a multi-agent control methodology for the optimal control of centralized air conditioning systems that are typically adopted in multi-zone commercial buildings. A hierarchical multi-agent framework is developed in which the agents cooperate to find the optimal operating point. Two consensus-based distributed optimization algorithms are formulated for this specific type of problem, which form the underlying mechanism of intra-agent optimization and interagent cooperation. Finally, a 3-zone building case study is used to demonstrate the performance of the proposed approach.

关键词： control agent INTEGRATED SHIP CONTROL optimization algorithms Buildings built structure Optimal control Air conditioning systems commercial buildings Control Methods Standing Orders Workstations Agents

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A Min-Max Control Synthesis for Uncertain Nonlinear Systems Based on Fuzzy T-S Model

A Min-Max Control Synthesis for Uncertain Nonlinear Systems ...

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IEEE International Conference Intelligent Systems

作者： Tatjana Kolemishevska-Gugulovska Mile Stankovski Imre J. Rudas Nan Jiang Juanwei Jing SS Cyril and Methodius University in Skopje Faculty of Electrical Eng. and Information Technologies Rugjer Boshkovik bb 1000 Skopje R. Macedonia School of Information Science & Robotics Obuda Univeristy H-1034 Budapest Hungary NEU College of Information Science & Engineering Liaoning Shenyang P.R. China

ISBN: (纸本)9781467322768

The min-max robust control synthesis for uncertain nonlinear systems is solved using Takagi-Sugeno fuzzy model and fuzzy state observer. Existence conditions are derived for the output feedback min-max control in the sense of Lyapunov asymptotic stability and formulated in terms of linear matrix inequalities. The convex optimization algorithm is used to obtain the minimum upper bound on performance and the optimum parameters of mini-max controller. The close-loop system is asymptotically stable under the worst case disturbances and uncertainty. Benchmark of inverted pendulum plant is used to demonstrate the robust performance within a much larger equilibrium region of attraction achieved by the proposed design.

关键词： Fuzzy T-S models fuzzy observer nonlinear systems optimum intelligent control robust control uncertainty Uncertain nonlinear system min-max control optimal parameter Robust control T-S fuzzy model Fuzzy optimization algorithms region of attraction

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Desynchronization for Decentralized Medium Access Control based on Gauss-Seidel Iterations

Desynchronization for Decentralized Medium Access Control ba...

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American Control Conference

作者： Daniel Silvestre Joao Hespanha Carlos Silvestre Instituto Superior Tecnico Universidade de Lisboa Lisboa Portugal University of California Santa Barbara CA 93106-9560 USA

ISBN: (纸本)9781538679012;9781538679265

We address the Desynchronization problem of achieving an equally spaced transmission schedule in a cooperative fashion. This problem arises in a shared medium communication and is of importance to achieve a fair multiple access schedule at the Medium Access Control (MAC) layer in the context of Wireless Sensor Networks (WSNs). In this paper, we investigate the convergence rate of different optimization algorithms and the potential benefits of addressing the problem as a solution of a set of linear equations. Initial results suggest that the Gauss-Seidel method can yield a faster convergence than previously proposed methods that employ a version of the Nesterov's method. Our approach also poses an interesting path for future research given the benefits of using other more advanced methods to solve systems of linear equations. Through simulations, we provide evidence to support future research on optimizing the parameter selection and also on categorizing the conditions under which one solution might be better in detriment of another.

关键词： Distributed control Communication networks optimization algorithms optimization algorithms networks(communications) decentralised control Gauss-Seidel method Medium access control Linear system of equations Linear equation

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