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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Song Jiakang Hu Mingli Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing 210016 Peoples R China

ISBN: (纸本)9781665442077

Aiming at the problem of modeling small sample systems with time-delay cumulative effects, this paper introduces a time-delay coefficient control term and a fractional cumulative generation operator, and proposes a fractional cumulative time-delay GM (1, N) grey prediction model, using particle swarm optimization algorithm to determine the model's optimal time-lag effect control coefficient and the optimal fractional cumulative generation order. Finally, combine the total economic output value and fixed asset investment of Zhejiang Province from 2003 to 2011 to establish a forecast model, and compare the prediction results of the GM (1, 1)., GM(1,N) and time-delay GM(1,N) models shows that the fractional cumulative time-delay GM(1,N) model can better solve the small sample multivariate with cumulative time-delay characteristics system prediction problem.

关键词： Grey Model Fractional accumulation Time-delay Particle swarm optimization algorithm

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Estimation of maize evapotranspiration in semi-humid regions of northern China using Penman-Monteith model and segmentally optimized Jarvis model

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JOURNAL OF HYDROLOGY 2022年 607卷

作者： Wu, Zongjun Cui, Ningbo Zhao, Lu Han, Le Hu, Xiaotao Cai, Huanjie Gong, Daozhi Xing, Liwen Chen, Xi Zhu, Bin Lv, Min Zhu, Shidan Liu, Quanshan Sichuan Univ Coll Water Resource & Hydropower State Key Lab Hydraul & Mt River Engn Chengdu 610065 Peoples R China China Agr Univ Coll Land Sci & Technol Key Lab Arable Land Conservat North China Minist Agr Beijing 100193 Peoples R China Northwest A&F Univ Key Lab Agr Soil & Water Engn Arid & Semiarid Area Minist Educ Yangling 712100 Peoples R China Chinese Acad Agr Sci Inst Environm & Sustainable Dev Agr State Engn Lab Efficient Water Use Crops & Disaste Key Lab Dryland Agr Beijing 100083 Peoples R China

Accurate estimation of maize evapotranspiration (ET) is of great significance for the improvement of crop water use efficiency and precision irrigation. The Penman-Monteith model (P-M) has been widely used to simulate crop ET. In the P-M model, the estimation accuracy of canopy resistance (r(c)) has a direct impact on ET. In this study, based on the eddy covariance system, large-scale lysimeter and meteorological station data from three sites (Yucheng, Yangling and Shangqiu) in semi-humid regions of northern China, the P-M model was applied to obtain canopy resistance (r(c)-(PM)) and correlation significances between r(c-PM )and different impact factors (R-n net radiation, T temperature, VPD saturated vapor pressure difference, theta soil moisture content, LAI leaf area index) were analysed. The whole growth period of maize was divided according to different LAI thresholds (0.1, 0.5, 1.0, 1.5, 2.0 and 3.0 m(2)m(- 2)). The Genetic algorithms (GA) and Differential Evolution (DE) algorithms were used to optimize the empirical parameters of the Jarvis model, and the P-M model was applied to estimate ET under different LAI thresholds at the three stations. The correlation significances of r(c-PM) with different influencing factors followed the order R-n > LAI > theta > VPD > T, and it was extremely significant with Rn (P < 0.01) and significant with LAI and theta (P < 0.05). The GA and DE algorithm optimization results showed that the calculation accuracy of r(c) was highest when LAI=0.5 m(2) m(- 2 )at Yucheng station, with R(2 )of 0.80 and 0.81, respectively, and when LAI=1.0 m(2) m(-2), and the accuracy of r(c) was highest at Yangling station, with R-2 of 0.87 and 0.89, respectively, and when LAI = 1.0 m(2) m( -2), and the accuracy of r(c) was highest at Shangqiu station, with R-2 of 0.84 and 0.84, respectively. Combined with P-M model to calculate maize ET under different LAI thresholds, the simulation accuracy of ET was best when LAI = 0.5 m(2 )m(-2 )at Yucheng stati

关键词： Penman-Monteith model optimization algorithm Jarvis model Leaf area index Segmentation Maize

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A novel hybrid algorithm based on Biogeography-Based optimization and Grey Wolf Optimizer

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APPLIED SOFT COMPUTING 2018年 67卷 197-214页

作者： Zhang, Xinming Kang, Qiang Cheng, Jinfeng Wang, Xia Henan Normal Univ Coll Comp & Informat Engn Xinxiang Henan Peoples R China Engn Technol Res Ctr Comp Intelligence & Data Min Xinxiang Henan Peoples R China

In order to obtain a Biogeography-Based optimization (BBO) algorithm with strong universal applicability, this paper presents a novel hybrid algorithm based on BBO and Grey Wolf Optimizer (GWO), named HBBOG. Firstly, BBO and GWO are improved respectively. For BBO, the mutation operator is got rid of and a differential mutation operation is merged into the migration operator to enhance the global search ability. The original migration operation is replaced by a multi-migration operation to enhance the local search ability. For GWO, the opposition-based learning approach is merged to prevent the algorithm from falling into the local optima to some degree. Then, the improved BBO and the opposition learning based GWO are hybridized by a new strategy, named single-dimensional and all-dimensional alternating strategy, to formulate HBBOG. HBBOG can effectively maximize the two algorithms' advantages and overall balance exploration and exploitation, therefore, it can obtain strong universal applicability. We make a large number of experiments on a set of various kinds of benchmark functions and CEC2014 test set and apply HBBOG to clustering optimization. The experimental results show that HBBOG outperforms quite a few state-of-the-art algorithms. (C) 2018 Elsevier B.V. All rights reserved.

关键词： optimization algorithm Evolutionary algorithm Biogeography-Based optimization Grey Wolf Optimizer Opposition-based learning approach

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Using Boundary Condition and Topology optimization to Design an Airplane Component

Using Boundary Condition and Topology Optimization to Design...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Persson, Johan A. Wiberg, Anton Linkoping Univ Management & Engn S-58183 Linkoping Sweden

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

This paper demonstrates a method that can be used to combine topology optimization with optimization of the boundary conditions. The method utilizes design of experiments and surrogate models to model how the boundary conditions affect the potential mass of the component. A demonstration of the method is made by applying it to design an airplane component and comparing the result to other approaches. The best design is then manufactured using additive manufacturing to verify that it is feasible.

关键词： Topology optimization Aeroplane Surrogate Model Design of Experiments Structural optimization optimization algorithm Finite Element Method Shape optimization Trusses Fuel Consumption

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Design of structure and control system of semiconductor refrigeration box

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Chinese Journal of Chemical Engineering 2020年第11期28卷 2792-2798页

作者： Meng Yu Zhiyun Zou Academy of Military Sciences Beijing 102205China

In order to create low temperature environment for the valve testing,a new type of semiconductor refrigeration box based on semiconductor refrigeration chip and programmable logic controller(PLC)control system is *** power of the semiconductor refrigeration chip is determined by calculating the heat dissipation characteristics of the semiconductor refrigeration *** natural convection heat dissipation with forced air cooling,the heat sink of semiconductor refrigeration chip is *** the control strategy,switch control is combined with an intelligent control *** single neuron optimization algorithm based on quadratic optimization is adopted to adjust and optimize the parameters of the proportional-integral-derivative(PID)controllers in real *** into account the limited hardware capabilities of the PLC,the Jacobian information in parameter adjustment is redesigned into a simplified form of *** actual test results of refrigeration box show good control performance.

关键词： Semiconductor refrigeration Structure design PLC optimization algorithm

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Improved genetic algorithm for optimal demand response in smart grid

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SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2022年 35卷

作者： Jeyaranjani, J. Devaraj, D. Kalasalingam Acad Res & Educ Dept Comp Sci & Engn Srivilliputhur Tamil Nadu India Kalasalingam Acad Res & Educ Dept Elect & Elect Engn Srivilliputhur Tamil Nadu India

In Smart Grid system, the consumers are provided with the opportunity to schedule their home appliances in response to variations in electricity price over time. This paper presents the optimal scheduling of resident ap-pliances. This optimal scheduling is formulated as an optimization problem and is solved by applying improved Genetic algorithm (GA). In this improved GA, the selection of chromosomes is carried out using entropy method, blended crossover and mutation is performed using correlation coefficient. The simulation is performed for a single resident load profile for a set of appliances using Python programming. The result shows the reduction in the electricity cost to that of the original. The number of iterations taken by the improved Genetic algorithm (GA) is comparatively lesser than the standard GA and the execution time is reduced by 2.76 s. Thus the result proves the effectiveness of the proposed improvisation in Genetic algorithm for optimal load scheduling.

关键词： Energy consumption Genetic algorithm Load scheduling Demand Response optimization algorithm Energy management system Real time pricing

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Low-sidelobe marine radar microstrip array antenna based on hybrid algorithm and metamaterial

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2022年第1期32卷

作者： Lin, Kangjian Fang, Shaojun Liu, Hongmei Dalian Maritime Univ Sch Informat Sci & Technol Dalian 116026 Peoples R China

A microstrip array antenna with low sidelobe level (SLL) for X-band marine radar is proposed. The antenna is composed of a 32-element patch array and a three-layer near-zero-index metamaterial (NZIM). The IABC-Kmeans algorithm, which combines the improved artificial bee colony algorithm and K-means clustering algorithm, is used to optimize the current amplitude of the array elements to obtain a lower SLL. The NZIM is loaded in front of the array antenna to reduce the beamwidth of the E-plane. The antenna is designed and fabricated. The measurement results show that the gain of the antenna at the center frequency is 22.7 dBi, the SLLs of H-plane and E-plane are -30.66 dB and - 26.78 dB respectively, and the half-power beamwidth of H-plane is 5.9 degrees. Compared with the previous similar antenna structures, the antenna has lower SLL under the premise of narrow beam and high gain, which is very suitable for X-band marine radar of small and medium fishing vessels.

关键词： low side lobe marine radar antenna metamaterials optimization algorithm

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Semantic communication-based convolutional neural network for enhanced image classification

Franklin Open

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Franklin Open 2024年 9卷

作者： Guler, Nivine Hazem, Zied Ben Department of Computer Science University of Central Asia Naryn 722918 Kyrgyzstan Automation and Sustainability Research Centre (ASRC) Department of Mechatronics Engineering College of Engineering (COE) University of Technology Bahrain Salmabad Bahrain

In AI-IoT environments, the traditional centralized cloud computing approach leads to high network transmission volumes and communication delays, negatively affecting intelligent task performance. This study addresses these issues by introducing an innovative semantic communication system model for intelligent tasks, leveraging deep learning techniques. The research focuses on image classification tasks constrained by bandwidth and delay in AI-IoT scenarios. The proposed model features a tailored semantic communication network architecture, where image feature maps are extracted on IoT devices. These semantic relations are then compressed based on the extracted feature maps to reduce power consumption on IoT devices and mitigate communication transmission pressures. Simulations and comparative analyses of various network performance metrics show that the proposed semantic communication system improves image classification accuracy by 90%% at low signal-to-noise ratios compared to traditional methods. With an 80%% compression ratio, the classification accuracy loss is minimal—within 2%%—when the signal-to-noise ratio exceeds 0. Additionally, at a signal-to-noise ratio of 20, the semantic compression transmission scheme enhances classification accuracy by 30%% compared to random compression. Moreover, the proposed system outperforms traditional approaches in execution time by approximately 80%%. © 2024 The Author(s)

关键词： CNN IoT optimization algorithm Semantic communication

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System Architecture Design Space Exploration: An Approach to Modeling and optimization

System Architecture Design Space Exploration: An Approach to...

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AIAA Aviation Forum

作者： Bussemaker, J. H. Ciampa, P. D. Nagel, B. DLR German Aerosp Ctr Inst Syst Architectures Aeronaut Hamburg Germany

ISBN: (数字)9781624105982

ISBN: (纸本)9781624105982

Systematic modeling of architecture design spaces is needed when architecting complex systems, to support experts in making less biased decisions, and to formulate the optimization problem needed to explore the large combinatorial design space. Existing methods do not offer enough compatibility with the Model-Based Systems Engineering (MBSE) approaches, cannot model all needed design scenarios, or are not flexible enough when it comes to architecture evaluation. A new method is presented that provides a semantic representation of the architecture design space, modeled as the Architecture Design Space Graph (ADSG). The ADSG represents three types of architectural decisions: function-component mapping, component characterization, and component connection. The ADSG is constructed from a design space definition, and discrete architectural decisions are automatically inserted according to specified rules. Once decisions and metrics have been defined, the hierarchical, mixed-integer, multi-objective optimization problem can be formulated: decisions are mapped to design variables, and performance metrics are mapped to objectives or constraints. An application of the method to the Apollo mission architecting problem is presented.

关键词： Space Exploration Model Based System Engineering Apollo Missions Earth Orbit Rendezvous optimization algorithm Crew Member Earth Centrifugal Pump Turbofan Multi Objective Evolutionary algorithms

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Discrete Adjoint Constrained Design optimization Approach for Unsteady Transonic Aeroelasticity and Buffet

Discrete Adjoint Constrained Design Optimization Approach fo...

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AIAA Aviation Forum

作者： Thomas, Jeffrey P. Dowell, Earl H. Duke Univ Dept Mech Engn & Mat Sci Durham NC 27708 USA

ISBN: (数字)9781624105982

ISBN: (纸本)9781624105982

We present the details of two primary research topics in the area of aeroelastic optimization that we are currently working on. The first topic is a new discrete adjoint aeroelastic design optimization solution methodology, which has a computational cost that is independent of the number of structural degrees-of-freedom of the aeroelastic model. In recent years, we have developed a discrete adjoint nonlinear harmonic balance frequency-domain unsteady aeroelastic design optimization methodology, which is able to compute aeroelastic geometric design gradients, that can then be used with an optimization solver to compute an alternate geometric design, which will delay the onset of flutter. This methodology has proven to be robust, however it can be computationally costly since the computational cost is proportional to the number of structural degrees-of-freedom. The new methodology we present does not have that issue, and only a single adjoint solution computation is required when design gradients are required by whatever optimization algorithm one happens to be using. The reason this is possible is that we have recently developed a new nonlinear harmonic balance frequency-domain based aeroelastic solution technique where both the aeroelastic solver and computational flow solver can be marched to convergence simultaneously. With our original aeroelastic solution methodology, we run the aeroelastic solver and flow solver sequentially, one after the other. With the ability to march the aeroelastic and flow solvers simultaneously, we automatically satisfy the constraints that the aeroelastic residual and flow solver residual are zero once the combined aeroelastic solver and flow solver is converged. The second topic discussed in this abstract are new transonic aeroelastic flutter and transonic buffet design optimization results that are computed using a constrained optimization solver. Previously, our transonic aeroelastic flutter and transonic buffet design optimization

关键词： Transonic Aeroelasticity Lift Over Drag Ratio Harmonic Balance Frequency Domain optimization algorithm Computing Angle of Attack Freestream Mach Number NACA 0012 Wind Tunnels

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