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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Zaid Nouna Hamid Bouyghf Mohammed Nahid Issa Sabiri Laboratory of Engineering Sciences and Biosciences Faculty of Sciences and Techniques Hassan II University Mohammedia Morocco Laboratory of Systems Signals and Artificial Intelligence ENSET Hassan II University Mohammedia Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Sudden cardiac arrest, frequently triggered by cardiac fibrillation, remains a significant global health concern. Defibrillation is a critical medical procedure that relies on precise electrical pulses to restore normal heart rhythm. To optimize pulse parameters, such as peak voltage and duration, we employ the Differential Evolution algorithm on a monophasic waveform. By utilizing the error between circuit simulation and targeted defibrillation parameters as an objective function, we aim to determine the optimal inductance and capacitance values of the defibrillator circuit. This approach enables the delivery of precisely tailored electrical shocks, potentially improving defibrillation success rates, reducing patient risk, and ultimately, contributing to advancements in cardiac care.

关键词： Inductance Power demand Heart beat Fibrillation Electric shock Circuit simulation Metaheuristics linear programming Circuit synthesis Defibrillation

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An Adaptive Class Topper Optimization for Scheduling Thermal Generation with Cubic Fuel Cost Function

An Adaptive Class Topper Optimization for Scheduling Thermal...

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Power, Energy and Electrical Engineering (CPEEE), International Conference on

作者： Pradeep Kumar Gupta Anju Kumari Gupta Kaur Tuttelberg Jako Kilter Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia Department of Mathematics Trinity B.Ed College (Baba Saheb Ambedkar Education University) West Bengal India

ISBN: (数字)9798331520090

ISBN: (纸本)9798331520106

This paper proposes a population-based metaheuristic optimization algorithm, i.e., an adaptive class topper optimization (ACTO), for solving cubic fuel cost objective functions economic load dispatch with equality and inequality constraints. The working principle of the proposed methodology is based on the learning improvement of students in a class for knowledge updating. In general, the use of polynomials function to represent generator fuel cost curves in real-time economic dispatch is an industry standard, and it significantly impacts the accuracy of the economic load dispatch solution. Many existing conventional methods struggle to deal with cubic fuel cost functions that reflect the non-linearity of the real generator response. Therefore, the proposed optimization technique is particularly efficient in solving non-linear higher-order objective functions for both smaller and larger generating units and it significantly decreases the computational time to obtain optimal fuel cost. The proposed algorithm has been successfully tested on the following dispatch case studies: 3 units, 26 units cubic fuel cost function without losses and 3 units cubic system with losses for different loading conditions. The results reveal that the adaptive class topper optimization algorithm outperform other existing methodology when addressing the higher-order generator cost functions.

关键词： Costs Metaheuristics Cost function linear programming Generators Real-time systems Power systems Fuels Thermal loading Standards

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Bector-Chandra type linear programming duality under fuzzy environment with parabolic concave membership functions

Bector-Chandra type linear programming duality under fuzzy e...

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Pratiksha Saxena Ravi Jain Department of Applied Mathematics Gautam Buddha University Greater Noida India Department of Mathematics Maharaja Agrasen Institute of Management Studies Rohini Delhi India

This paper presents the study of a pair of primal-dual fuzzy linear programming and establishes duality results. It is based on parabolic concave membership functions. Choice of parabolic concave membership functions makes it unique and leads to the nonlinear programming. Duality results have been established using the aspiration level approach. A numerical example is also taken to demonstrate the approach and verification of results.

关键词： linear programming programming Industries Standards Games Educational institutions

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Scalable computation of causal bounds

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 11224-11259页

作者： Madhumitha Shridharan Garud Iyengar Department of Industrial Engineering and Operations Research Columbia University New York City NY

We consider the problem of computing bounds for causal queries on causal graphs with unobserved confounders and discrete valued observed variables, where identifiability does not hold. Existing non-parametric approaches for computing such bounds use linear programming (LP) formulations that quickly become intractable for existing solvers because the size of the LP grows exponentially in the number of edges in the causal graph. We show that this LP can be significantly pruned, allowing us to compute bounds for significantly larger causal inference problems compared to existing techniques. This pruning procedure allows us to compute bounds in closed form for a special class of problems, including a well-studied family of problems where multiple confounded treatments influence an outcome. We extend our pruning methodology to fractional LPs which compute bounds for causal queries which incorporate additional observations about the unit. We show that our methods provide significant runtime improvement compared to benchmarks in experiments and extend our results to the finite data setting. For causal inference without additional observations, we propose an efficient greedy heuristic that produces high quality bounds, and scales to problems that are several orders of magnitude larger than those for which the pruned LP can be solved.

关键词： causal bounds partial identification of causal effects causal bounds with observations multi-cause setting with unobserved confounders linear programming

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Multi-Child DE - a Massively Parallel Differential Evolution Algorithm

Multi-Child DE - a Massively Parallel Differential Evolution...

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Computational Intelligence on Engineering/Cyber Physical Systems (CIES), IEEE Symposium on

作者： Rainer Storn Kenneth V. Price Radiocommunications Systems Division Rohde & Schwarz GmbH & Co. KG Muenchen Germany Unaffiliated Vacaville C.A. U.S.A.

ISBN: (数字)9798331508272

ISBN: (纸本)9798331508289

To optimize objectives that require extensive simulations, engineers need a powerful algorithm that can run in parallel to minimize wall-clock time. Evolutionary algorithms excel in both regards: they are powerful optimizers that can be implemented in parallel by assigning one processor to each population member. This paper, however, addresses the question: How can we minimize a simulation's wall-clock time if we have many more processors than there are population members? Our solution is the multi-child differential evolution (MCDE) algorithm in which each parent competes against more than one child. We benchmarked the scaling performance of the MCDE version of classic DE with a test bed of ten functions. We also compared MCDE to a parallel CMA-ES variant with three of our test bed's functions. Results from both experiments show that MCDE achieves a significant speedup that scales well with the number of processors.

关键词： Multicore processing Evolutionary computation Benchmark testing linear programming Optimization

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Locally linear Embedding Based on Scrambled Halton Sequence Initialized Frilled Lizard Optimization

Locally Linear Embedding Based on Scrambled Halton Sequence ...

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IEEE Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Qihua Guo Jiashu Wang Longhui Hou Nengwei Lei Dan Li Wei Nai Zan Yang School of Electronic Information Huzhou College Huzhou China Huzhou Key Laboratory for Urban Multidimensional Perception and Intelligent Computing Huzhou College Huzhou China Public Teaching and Research Department Huzhou College Huzhou China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

In the era of big data, the scale and complexity of data are ever increasing, traditional data dimensionality reduction methods can no longer meet the requirements of data users. In this context, manifold learning has now become an important research direction, which mainly achieves dimensionality reduction and mapping of nonlinear structural data in high-dimensional space to low-dimensional space, reduces data noise, and improves low-dimensional data representation ability. Locally linear embedding (LLE) is an important algorithm in manifold learning that projects data from high-dimensional space onto low-dimensional space while maintaining the linear relationship between data. However, the optimization objective function of LLE uses L2 norm measurement to approximate the error, which can easily amplify or reduce the error and cause oscillation in the error measurement. Therefore, in this paper, L1 norm instead of L2 norm is used to overcome this drawback, but introduces a new problem of the objective function becoming a non-smooth function. To solve this problem, in this paper, a derivative-free optimization method, which is also a swarm intelligence method called scrambled Halton sequence initialized frilled lizard optimization has been proposed, and via numerical experiment, its reliability and effectiveness has been verified.

关键词： Mechatronics Measurement uncertainty Noise Optimization methods linear programming Manifold learning Reliability Particle swarm optimization Information technology Oscillators

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Solving the Balance Optimization Problem of Makespan and Total Computation Time for Cloud Computing Scheduling Based on NSGA-II

Solving the Balance Optimization Problem of Makespan and Tot...

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Digital Analysis and Processing, Intelligent Computation (DAPIC), International Conference on

作者： Can Wu Dan Liu College of Computer Science and Technology Changchun University of Science and Technology Changchun China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

In the context of industrial upgrading, the exponential growth of computational demands for big data processing has emerged as a critical challenge. Cloud computing, with its evolving technological capabilities, presents a viable solution to address these escalating computational requirements. This study focuses on optimizing resource allocation efficiency through the establishment of a multiobjective optimization framework for cloud computing systems. Specifically, we formulate mathematical representations of objective functions and constraints while detailing corresponding encoding/decoding methodologies. The research employs the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to resolve task scheduling dilemmas in cloud environments, simultaneously optimizing makespan and total computational time through innovative applications of nondominated sorting and congestion distance comparison. A series of multi-scale comparative experiments demonstrate the algorithm's superior performance over conventional scheduling approaches.

关键词： Cloud computing Job shop scheduling Processor scheduling Optimization models linear programming Computational efficiency Resource management Optimization Sorting Convergence

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Enhancing Boundary-Handling Strategies for Convolutional Sparse Representation Model with 46 × 46 Convolution-Multiplication Properties

Enhancing Boundary-Handling Strategies for Convolutional Spa...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuto Tsukiashi Yoshimitsu Kuroki National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Convolutional sparse representation (CSR) extends the standard form by incorporating convolutional operations and has achieved notable success in image processing applications, offering a shift-invariant representation model. Recent studies typically redesign the initial model by exploiting the convolution-multiplication property of the discrete Fourier transform to solve the involved convex optimizations efficiently, which imposes periodic boundary handling and risks introducing boundary artifacts. This paper generalizes this approach by leveraging 46 × 46 convolution-multiplication properties while requiring only extra element-wise operations, enabling model designs that combine periodic, antiperiodic, and 40 symmetric boundary handlings for each dimension and across convolutions. These newly accepted models demonstrated better representation performance than the conventional model in our experiments, indicating the benefits of selecting appropriate boundary handlings.

关键词： Convolution Sparse approximation Computational modeling Image processing Memory management Transforms linear programming Convex functions Speech processing Standards

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Situational Awareness Based Resource Allocation for Multi-Target Tracking in Distributed Radar Network

Situational Awareness Based Resource Allocation for Multi-Ta...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Mushen Lin Fenggang Yan Lingda Ren Xiangtian Meng Maria Greco Fulvio Gini Ming Jin School of Information Science and Engineering Harbin Institute of Technology Weihai China Department of Electrical and Electronic Engineering The University of Hong Kong China Department of Information Engineering University of Pisa Italy

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, we present a Situational Awareness based Resource Allocation (SA-RA) strategy for multi-target tracking (MTT) in distributed radar networks, where both the resource utilization and overall MTT accuracy can be improved. The fusion rule with probabilistic data association (PDA) is used to associate cumulative data with measurement data from radar nodes. We also further derive the Bayesian Cramér-Rao Lower Bound (BCRLB) under the PDA fusion rule. For the proposed SA-RA strategy, the targets behavior is analyzed to determine their importance weights, expected tracking accuracy, and the allocated beams for each target. Utilizing the PDA-BCRLB and the importance weights, the objective function of the SA-RA strategy is formulated as a weighted sum of target utility functions. By addressing this objective function, the optimal transmission power is determined. Simulation results verify the superiority both in terms of tracking performance and resource allocation.

关键词： Target tracking Accuracy Radar measurements Simulation Radar Radar tracking linear programming Bayes methods Acoustic beams Resource management

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Feedback Indicators for Providing Carbon Impact of Vehicle Charging to Electric Vehicle Users

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Transportation Research Procedia 2023年 70卷 347-355页

作者： Nana Kofi Twum-Duah Lucas Hajiro Neves Mosquini Muhammad Salman Shahid Frédéric Wurtz Benoît Delinchant Univ. Grenoble Alpes CNRS Grenoble INP G2Elab F-38000 Grenoble France Univ. Grenoble Alpes CNRS Grenoble INP G-SCOP F-38000 Grenoble France University of Applied Sciences of Western Switzerland Energy Institute HEIA-FR 1700 Fribourg Switzerland

The purpose of this article is to introduce two indicators designed to evaluate and consequently influence the indirect emissions related to the operation of an EV. The first indicator, denoted as “Electric Vehicle CarbonFlex Potential” indicator, evaluates an EV's maximum and minimum achievable carbon emissions using an optimization approach and compares the user's resultant indirect carbon emissions to these boundaries, therefore, this indicator compares the users behavior to the optimal best and worst cases. The second indicator is “EcoCharge Time” indicator, which provides feedback to an EV user based on their charging behavior on the best and worst times of charging the vehicle in a day. Since human behavior cannot be controlled, such indicators are essential tools for influencing the behavior of EV users toward a desired optimal, in this case, a charging schedule with the lowest possible overall indirect emissions. The proposed indicators were tested on an EV dataset using the carbon intensity data from a number of countries and the results show that there exists considerable flexibility potential. Additionally, the results also showed the best charging times, which were typically clustered around, allowing for ease of use and understanding.

关键词： Indirect Carbon Emissions Energy Transition Carbon-free Transportation Feedback Indicators linear programming

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