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3rd International Conference on Pattern Analysis and Image Analysis (IPRIA)

作者： Khademi, Ghassem Ghassemian, Hassan Tarbiat Modares Univ Fac Elect & Comp Engn Image Proc & Informat Anal Lab Tehran Iran

ISBN: (纸本)9781509064540

This paper proposes a multi-objective approach to improving the component substitution (CS) based pansharpening method by obtaining the adaptive weights. The non-dominated sorting genetic algorithm ii (NSGA-ii) is employed to simultaneously optimize two objective functions. The inverse of the Correlation Coefficient (CC) and a weighted sum of the Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) in the spectral and spatial domains are used as the objective functions. The use of a multi-objective approach in the CS technique allows optimizing the fused image in terms of both spatial and spectral resolutions. Simulation results show that the proposed method outperforms popular CS-based fusion methods.

关键词： pansharpening component substitution multi-objective optimization non-dominated sorting genetic algorithm ii

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Studying the Geographical Cluster Paging with Delay Constraint in Registration Areas with the algorithm NSGAii 18

Studying the Geographical Cluster Paging with Delay Constrai...

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18th European Conference on Applications of Evolutionary Computation (EvoApplications) as part of EvoSTAR Conference

作者： Berrocal-Plaza, Victor Vega-Rodriguez, Miguel A. Sanchez-Perez, Juan M. Univ Extremadura Escuela Politecn Dept Comp & Commun Technol Campus Univ S-N Caceres 10003 Spain

ISBN: (纸本)9783319165486;9783319165493

The mobility management strategy based on registration areas is one of the most popular strategies to manage the subscribers' mobility in current Public Land Mobile Networks. For it, the network cells are arranged in continuous and non-overlapped sets in order to partially track the subscribers' movement. In this way, the network knows the location of its subscribers at a registration area level and the paging should only be performed in the cells within the last updated registration area. The paging scheme studied in this work is the geographical cluster paging, a probabilistic paging in which it is assumed that the probability of finding a mobile station (i.e. the subscriber's terminal) decreases as we move away from the last updated network cell following a normal distribution. The main appeal of this paging scheme is that we can considerably reduce the signaling traffic (with respect to the simultaneous paging) without including new elements in the network. Furthermore, we analyze it for different probability thresholds and considering delay constraints. On the other hand, we use our implementation of the non-dominated sorting genetic algorithm ii (NSGAii) with the aim of finding the best possible sets of non-dominated solutions. Results show that each probability threshold has its own non-dominated region in the objective space, and that the signaling traffic can be reduced by about 30% (with respect to the simultaneous paging).

关键词： Geographical cluster paging Registration areas Multiobjective optimization non-dominated sorting genetic algorithm ii

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Distributed Energy Resources and Fast Charging Stations Allocation for Enhanced System Operation and Charging Infrastructure Coverage 15

Distributed Energy Resources and Fast Charging Stations Allo...

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15th Seminar on Power Electronics and Control (SEPOC)

作者： Ferraz, Rafael S. F. Ferraz, Renato S. F. Junior, Vanio F. S. Rueda-Medina, Augusto C. Fardin, Jussara F. Univ Fed Espirito Santo PPGEE Postgrad Program Elect Engn Vitoria ES Brazil

ISBN: (纸本)9798350312898

The growing insertion of Electric Vehicles (EVs) in the distribution system is a promising solution to mitigate the greenhouse emission issue. However, as the number of EVs significantly increases, the excessive charging demand of Fast Charging Stations (FCSs) may lead to instability problems in the distribution network. Therefore, this paper proposes a multi-objective optimization approach for the allocation and sizing of Fast Charging Stations (FCSs) with the objective of minimizing their installation and operation costs, while maximizing the coverage for EVs. It is well-known that the integration of EVs results in increased power losses. As a consequence, in this study, an optimized planning of Distributed Energy Resources (DERs) was also performed with the purpose of mitigating this issue. The non-dominated sorting genetic algorithm ii (NSGA-ii) was applied to obtain the Pareto curve, which made it possible to minimize the objective functions for the 33-bus test feeder and 25-node transportation network, considering commercial and residential areas. Based on the solution selected by the Fuzzy Decision-Making method, it was possible to minimize the voltage deviation even with the insertion of the FCSs in the system.

关键词： Distributed Energy Resource Fast Charging Station Maximal coverage non-dominated sorting genetic algorithm ii Power Quality Indices

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Research on Site Selection of Rescue Sites at Sea Based on NSGA ii 2

Research on Site Selection of Rescue Sites at Sea Based on N...

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2nd IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Chen, Mingzhang Liu, Jingxian Li, Zhaozhang Ma, Weihao Sun, Zheng WUT Wuhan Hubei Peoples R China

ISBN: (纸本)9781509044993

To reduce the loss caused by marine sudden accidents, proper emergency rescue sites are indispensable for improving response and rescue capabilities. It's necessary to analyze the marine accidents and the types of emergency resources, establish emergency resource stations location model which can be used to determine the number and distribution of the emergency resource stations. Then, we can allocate the resources to corresponding emergency sites based on the relief supplies demand in waters of incident. An improved non-dominated sorting genetic algorithm ii with elite strategy is used to solve some problem about location, making the emergency sites covering as much waters with potential dangers as possible. The case analysis shows that the maritime emergency rescue sites, selected from the emergency rescue selection site which based on the NSGA, can cover all demand points and meet the requirements of "fairness" and "efficiency". In this paper, the research is of considerable theoretical and practical value in optimizing emergency resource distributions of marine incidents.

关键词： emergency resource stations location model the emergency resource distribution sudden accident non-dominated sorting genetic algorithm ii

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Multi-Objective Optimization for Automated Business Process Discovery 11

Multi-Objective Optimization for Automated Business Process ...

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11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K) / 11th International Conference on Knowledge Discovery and Information Retrieval (KDIR)

作者： Ghazal, Mohamed A. Ghoniemy, Samy Salama, Mostafa A. British Univ Egypt Dept Comp Sci Cairo Egypt

ISBN: (纸本)9789897583827

Process Mining is a research field that aims to develop new techniques to discover, monitor and improve real processes by extracting knowledge from event logs. This relatively young research discipline has evidenced efficacy in various applications, especially in application domains where a dynamic behavior needs to be related to process models. Process Model Discovery is presumably the most important task in Process Mining since the discovered models can be used as an objective starting points for any further process analysis to be conducted. There are various quality dimensions the model should consider during discovery such as Replay-Fitness, Precision, Generalization, and Simplicity. It becomes evident that Process Model Discovery, with its current given settings, is a Multi-Objective Optimization Problem. However, most existing techniques does not approach the problem as a Multi-Objective Optimization Problem. Therefore, in this work we propose the use of one of the most robust and widely used Multi-Objective Optimizers in Process Model Discovery, the NSGA-ii algorithm. Experimental results on a real life event log shows that the proposed technique outperforms existing techniques in various aspects. Also this work tries to establish a benchmarking system for comparing results of Multi-Objective Optimization based Process Model Discovery techniques.

关键词： Multi-Objective Optimization Process Mining Multi-Objective Evolutionary algorithms Process Model Discovery non-dominated sorting genetic algorithm ii

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Optimal drug scheduling for cancer chemotherapy using two degree of freedom fractional order PID scheme

Optimal drug scheduling for cancer chemotherapy using two de...

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4th International Symposium on Intelligent Systems Technologies and Applications (ISTA)

作者： Panjwani, Bharti Mohan, Vijay Rani, Asha Singh, Vijander Univ Delhi Netaji Subhas Inst Technol Div Instrumentat & Control Engn New Delhi 110078 India

This article presents optimal drug scheduling in chemotherapeutic treatment for eradication of cancerous cells while maintaining tolerable toxicity for the complete period of treatment. For this purpose a cascade control technique is designed wherein individual 2DOF FOPID controllers are employed to regulate drug concentration and toxicity. Conventional schemes fail to address the needs of divergent objectives of cancer chemotherapy which motivates the authors to employ a multi-objective optimization technique, NSGA-ii to optimally tune the controller parameters. 2DOF FOPID, its integer order counterpart and PID control schemes are tested on cancer patient model for comparative analysis. The performance of proposed controller is evaluated on the basis of number of cancer cells and normal cells remaining at the end of treatment. Further robustness of the controller is analysed for parametric uncertainty in patient model and disturbance in infusion pump which affects the input drug dosages. The results reveal that proposed control scheme provides optimal drug scheduling and is significantly robust in the presence of uncertainty and disturbances.

关键词： Two degree of freedom-fractional order PID controller cancer chemotherapy non-dominated sorting genetic algorithm ii robustness testing

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Research on the Multi-objective Optimization Model of System-level BIT Testability Index Determination

Research on the Multi-objective Optimization Model of System...

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2nd International Conference on Frontiers of Manufacturing and Design Science (ICFMD 2011)

作者： Zhu, Chunsheng Zhang, Qi Su, Fantun Ran, Hongliang PLA Univ Sci & Tech Engn Inst Corps Engineers Nanjing 210007 Jiangsu Peoples R China

ISBN: (纸本)9783037852828

By weighing reliability, maintainability, availability and life-cycle cost of equipment which are influenced by testability, the testability indexes of system level BIT are determined on the basis of maximum system reliability & maintainability and minimum the life-circle cost. The influence mathematical models of system reliability, maintainability, availability and life-circle cost are established. According to these mathematical models, the multi-objective optimization model of system-level BIT testability indexes is established. The multi-objective optimization model is solved using non-dominated sorting genetic algorithm ii, and the validity of the multi-objective optimization model is proved through an example.

关键词： Multi-object Optimization Model Built-in Test Testability Index Design for Testability non-dominated sorting genetic algorithm ii

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Preference Driven Multi-objective Optimization of Beam Pumping Process 8

Preference Driven Multi-objective Optimization of Beam Pumpi...

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8th International Symposium on Computational Intelligence and Design (ISCID)

作者： Gao Lun Gu Xiao-hua Wang Kan Li Tai-fu Chongqing Univ Sci & Technol Coll Elect & Informat Engn Chongqing 401331 Peoples R China Xian Shiyou Univ Sch Elect Engn Xian 710065 Peoples R China

ISBN: (纸本)9781467395878

Obtaining optimal decision parameters has significant meaning to improve the beam pumping process's inefficiency and energy-intensity. However, affected by uncertainties from mechanism, geological environment and human, it is hard to grasp the relationships among the operation parameters, the environment variables and the performances. This paper proposes a preference driven multi-objective optimization method to achieve optimal decision parameters based on neutral network model. First, using back propagation neutral network to find beam pumping system's latent rule represented by a model. Furthermore, constructing the preference function of oil yield, and finally using non-dominated sorting genetic algorithm ii to optimize the preference driven multi-objective optimization problem which reaches the optimal decision parameters. The experimental results show that the optimal decision parameters can reduce the energy consumption about 15.87%, which proves the feasibility and effectiveness of the proposed method.

关键词： preference driven multi-objective optimization back propagation neutral network non-dominated sorting genetic algorithm ii decision parameters beam pumping process

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Optimizing frequencies of functionally graded material plates via multi-objective genetic algorithm: Positioning point supporters for maximum performance

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AEROSPACE SCIENCE AND TECHNOLOGY 2024年 154卷

作者： Cai, Liang Wu, Zhixin Gao, Zunhai Hubei Univ Automot Technol Sch Econ & Management Shiyan 442002 HuBei Peoples R China Zhejiang Univ Finance & Econ DONGFANG Coll Coll Business Adm Haining 314408 Zhejiang Peoples R China Zhejiang Univ Finance & Econ Coll business Adm Hangzhou 310018 Zhejiang Peoples R China Nanchang Inst Sci & Technol Sch Informat & Artificial Intelligence Nanchang 330108 Jiangxi Peoples R China

In the presented study, an approach is introduced for optimizing the vibrational characteristics of aerospace structures that are composed of Functionally Graded Materials (FGM). The focus is placed on the strategic positioning of point supporters to enhance the structural performance under various operational conditions. The effective elasticity properties of the FGMs are determined using the Mori-Tanaka method for homogenization. The deformation behavior of these structures is analyzed by employing the first-order shear deformation theory. Solutions are computed through the 2D Ritz method, which utilizes Chebyshev polynomials, forming the basis for the objective function of a multi-objective genetic algorithm. This algorithm is designed to optimize the positioning and the number of point supporters aimed at targeting specific vibration frequencies. The non-dominated sorting genetic algorithm ii (NSGA-ii) is utilized to efficiently generate Pareto optimal solutions, which illustrate the trade-offs between conflicting objectives. The validation of the solution method is achieved through comparisons with experimental data, confirming the accuracy and practical relevance of the approach. The application of the optimization framework is extended to various configurations of aerospace structures, including diverse compositions of FGM and different boundary conditions. This methodology is shown not only to enhance the operational performance of aerospace structures but also to contribute to the precise design and manufacturing of components in aircraft and satellites, aligning with the central interests of aerospace engineering.

关键词： Multi-frequency optimization non-dominated sorting genetic algorithm ii Chebyshev-based Ritz Method Optimal point supports placement FGM plates

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BIM-based estimation of inputs for site layout planning and locating irregularly shaped facilities

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AUTOMATION IN CONSTRUCTION 2022年 141卷

作者： Zavari, Masoud Shahhosseini, Vahid Ardeshir, Abdollah Sebt, Mohammad Hassan Amirkabir Univ Technol Dept Civil & Environm Engn 350 Hafez AveValiasr Sq Tehran Iran

Although construction site layout planning (CSLP) is a significant step in construction planning that has a direct impact on the project performance, its input parameters are mainly obtained by asking site managers and related contractors. The dynamic environment, complexities, and uncertainties of a construction project cause a reduction in the precision of these inputs. This study aims to enhance the CSLP precision by providing a holistic and practical method for estimating these parameters. For this intention, a database is established using the data obtained from the project schedule and BIM to allow the calculation of the input parameters. A new algorithm for facility setup is also proposed for optimizing the facility's shape, which seems beneficial in congested sites where space becomes a limited resource. A case study demonstrates the practicality and functionality of the method. The facility setup algorithm also causes an improvement over restricting facilities to regular shapes.

关键词： Construction site layout planning (CSLP) Building Information Modeling (BIM) Congested sites Input parameters Facility setup algorithm non-dominated sorting genetic algorithm ii (NSGA-ii)

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