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Assessment of Effective Monitoring Sites in a Reservoir Watershed by Support Vector Machine Coupled with multi-objective genetic algorithm for Sediment Flux Prediction during Typhoons

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WATER RESOURCES MANAGEMENT 2021年第8期35卷 2387-2408页

作者： Jhong, Bing-Chen Fang, Hsi-Ting Huang, Cheng-Chia Natl Taiwan Univ Sci & Technol Dept Civil & Construct Engn Taipei 106335 Taiwan Taiwan Integrated Disaster Prevent Technol Engn C New Taipei 236654 Taiwan Natl Taipei Univ Business Ctr Gen Educ Taipei 100026 Taiwan

Effectively assessing crucial monitoring sites with suspended sediment concentration (SSC) is a vital challenge for achieving accurate prediction of sediment flux on sluice gates at a dam in a reservoir watershed. To address this issue, an assessment framework based on a core concept of Data-Information-Knowledge-Wisdom (DIKW) hierarchy is proposed in this study. First, for the reasonable training of the coupled method, a two-dimentional layer-averaged density current model, SRH2D, is applied to simulate reasonable SSC data. The limited SSC data at monitoring sites collected from the field and at dam face, inflow, and outflow discharges are collected for validation of a calibrated numerical model. Second, a well-known data-driven method, Support Vector Machine (SVM), is coupled with multi-objective genetic algorithm (MOGA) as a sediment-flux-prediction (SFP) model in the proposed framework to evaluate effective monitoring sites with SSC. An application in the Shih-Men Reservoir is implemented to demonstrate the contribution of the proposed investigation framework. The results indicate that the spatial turbidity current movement is reasonably simulated by the numerical model and appropriate as reliable data for the SFP model. The SSCs at measured points located on the lower level at dam face are significantly higher. Moreover, the results also show that the simulated SSC at the monitoring sites located near the inflow point and dam face are relatively useful for SFP. The analyzed results are concluded that the well-established observation equipment at the inflow point and near the dam is necessary for obtaining high-quality measured data, which has become a significant key issue on reservoir operation management (ROM). Also, the proposed framework is expected to be helpful to improve the benefit of ROM as reference for decision makers.

关键词： Sediment flux prediction Suspended sediment concentration Reservoir Support vector machine multi-objective genetic algorithm Typhoon

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Horizontal inventory coordination in supply chain based on multi-objective genetic algorithm

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第4期37卷 4803-4810页

作者： Pang, Hui Dong, Shaohua Zhang, Xinwei Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China

In this paper, under the circumstance of uncertain customer demand, the enterprises on the same node in multiple supply chains conduct horizontal inventory coordination according to their own inventory and demand. Based on the combination of horizontal inventory replenishment and vertical normal replenishment, the related mathematical model has been established. By studying the inventory strategy in the decentralized and centralized decision-making, the dual marginalization effects are found in the network system composed of multiple supply chain. So the revenue sharing contract is introduced to solve this problem. It has been found in the study that after adopting the horizontal inventory coordination mechanism of the supply chain, the profit of the members in the supply chain system and the overall profit of the system are both higher than those which didn't adopt the mechanism. The improved multi-objective genetic algorithm is used to calculate and verify the problem. In particular, after the revenue sharing contract is adopted, the profits are further enhanced.

关键词： Inventory coordination economic order quantity inventory strategy revenue sharing multi-objective genetic algorithm

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Integration of a fuzzy neural network and multi-objective genetic algorithm for optimisation of BLU light guide plate injection moulding parameters

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INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY 2012年第1-4期45卷 83-95页

作者： Wang, Shen-Tsu Natl Pingtung Inst Commerce Commerce Automat & Management Dept Pingtung 900 Taiwan

Backlight module unit (BLU) is a key component of LCD, and thinning of the BLU light guide plate is the focus of development. Most light guide plates are manufactured using the injection moulding process. The experimental design in this study is the most common research approach applied in the setting of light guide plate parameters. However, the parameter interaction and system non-linearity can easily result in prediction errors of parameters. Meanwhile, since the optimal moulding conditions have not been achieved, the best effects of display illumination and brightness cannot be achieved. Hence, this study first applied the grey relational sorting method to determine the major control factors influencing the BLU light guide plate, and then built the approximate model of a fuzzy neural network, according to experimental planning samples, before using the multi-objective genetic algorithm to determine the optimal manufacturing parameter design. The results suggested that the process capability index C-pk value of the light guide plate X-axis size is improved from 0.43 to 1.56, and has stabilised product quality and enhanced process capability. This study proved that the prediction model of process optimisation, as obtained by using this research method, is effective.

关键词： fuzzy neural network multi-objective genetic algorithm process capability index BLU light guide plate

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Optimization investigation on configuration parameters of spiral-wound heat exchanger using genetic Aggregation response surface and multi-objective genetic algorithm

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APPLIED THERMAL ENGINEERING 2017年 119卷 603-609页

作者： Wang, Simin Jian, Guanping Xiao, Juan Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

Based on the method combining genetic Aggregation response surface and multi-objective genetic algorithm, the effects of configuration parameters of spiral-wound heat exchanger (SWHE) on flow and heat transfer characteristics were numerically studied. The results show that the shell-side pressure drop of the spiral-wound heat exchanger decreases with the increase of layer pitch, winding angle and tube pitch, respectively. The shell-side heat transfer coefficient of the spiral-wound heat exchanger decreases with the increase of layer pitch and increases with the external diameter of tube. The shell-side heat transfer coefficient increases firstly with the increase of the winding angle and then decreases. The sensitivity analysis also shows that the shell-side flow and heat transfer characteristics are mainly affected by the winding angle. Under the working condition, the pressure drop and heat transfer coefficient are both negatively correlated with the layer pitch. And the winding angle is negatively correlated with the pressure drop, but positively correlated with the heat transfer coefficient. Three optimal configurations were obtained by the multi-Object genetic algorithm based on genetic Aggregation response surface. Compared with the original configuration, the average heat transfer coefficient of improved ones is enhanced by 2.93%, while the average pressure drop is reduced by 40.27%. The results are of great significance for the design of spiral-wound heat exchanger. (C) 2017 Published by Elsevier Ltd.

关键词： Spiral-wound heat exchanger Structural parameters genetic Aggregation multi-objective genetic algorithm

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A multi-objective genetic algorithm for a special type of 2D orthogonal packing problems

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APPLIED MATHEMATICAL MODELLING 2020年第Part1期77卷 66-81页

作者： Erozan, Ihsan Caliskan, Enes Kutahya Dumlupinar Univ Kutahya Turkey

In this study, a multi-objective model is proposed for a specific two-dimensional orthogonal packing problem. The model has three objectives, namely: (i) to minimise the distances between the centres of rectangular items, (ii) to use a minimisation function to place the related rectangular items close to each other, and (iii) to minimise the area of each rectangular item that falls outside of the radius. In addition to the weighted-sum method, the model uses the conic scalarisation method for scalarisation of the nonlinear multi-objective optimisation problem. The proposed model is a hybridisation of a placement procedure and a multi-objective genetic algorithm, and introduces the concept of the defensive radius to the literature. The model is tested on a randomly generated set of instances and some test problems. The computational results validate the quality of the solutions and the effectiveness of the proposed multi-objective model compared to the cluster boundary algorithm. Besides, the results show that the conic scalarisation outperforms the weighted-sum method in terms of scalar results in most cases. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Orthogonal packing problem multi-objective genetic algorithm Defensive radius Conic scalarisation

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An improved multi-objective genetic algorithm for heterogeneous coverage RFID network planning

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第8期54卷 2227-2240页

作者： Tang, Lin Zheng, Li Cao, Hui Huang, Ningjian Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Gen Motors R&D Mfg Syst Res Lab Warren MI USA

Recent research has demonstrated the potential benefits of radio frequency identification (RFID) technology in the supply chain and production management via its item-level visibility. However, the RFID coverage performance is largely impacted by the surrounding environment and potential collisions between the RFID devices. Thus, through RFID network planning (RNP) to achieve the desired coverage within the budget becomes a key factor for success. In this study, we establish a novel and generic multi-objective RNP model by simultaneously optimising two conflicted objectives with satisfying the heterogeneous coverage requirements. Then, we design an improved multi-objective genetic algorithm (IMOGA) integrating a divide-and-conquer greedy heuristic algorithm to solve the model. We further construct a number of computational cases abstracted from an automobile mixed-model assembly line to illustrate how the proposed model and algorithm are applied in a real RNP application. The results show that the proposed IMOGA achieves highly competitive solutions compared with Pareto optimal solutions and the solutions given by four recently developed well-known multi-objective evolutionary and swarm-based optimisers (SPEA2, NSGA-II, MOPSO and (MOPSO)-O-2) in terms of solution quality and computational robustness.

关键词： heterogeneous coverage RFID network planning multi-objective genetic algorithm mixed-model assembly line

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Zonal control for selective catalytic reduction system using a model-based multi-objective genetic algorithm

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INTERNATIONAL JOURNAL OF ENGINE RESEARCH 2021年第3期22卷 911-920页

作者： Wang, Guoyang Qi, Jinzhu Liu, Shiyu Li, Yanfei Shuai, Shijin Wang, Zhiming Shandong Univ Sch Energy & Power Engn Jinan Shandong Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China

It is challenging for aqueous urea injection control to achieve high NOconversion efficiency while restricting tailpipe ammonia (NH3) slip. Optimizing the selective catalytic reduction systems can reduce diesel engine emissions, potentially improve fuel economy and urea utilization efficiency, and finally reduce aftertreatment costs. In this article, a model-based multi-objective genetic algorithm is adopted to optimize selective catalytic reduction systems related to trade-off between NOemission and NH3 slip. Selective catalytic reduction model is a one-state selective catalytic reduction model based on continuous stirred tank reactor theory, which significantly reduces the computational burden. The optimal NH3 coverage ratio map was obtained globally based on world harmonized transient cycle. The effect of temperature on optimal NH3 coverage ratio, Zonal control logics extracted from the optimal solution, and the control problems on different zones were analyzed. The zonal control logics were validated on multiple test cycle with different initial NH3 coverage ratios. Results show that the zonal control achieves high NOconversion while restricting the tailpipe NH3 slip. With this method, NOemission and NH3 slip of optimal solution can meet the requirements of the Euro VI emission regulation for heavy-duty diesel engines.

关键词： Heavy-duty diesel engine NO emission control selective catalytic reduction ammonia coverage ratio optimization multi-objective genetic algorithm

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CFD modeling and optimization of a latent heat storage unit for running a solar assisted single effect Li-Br absorption chiller using multi-objective genetic algorithm

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SUSTAINABLE CITIES AND SOCIETY 2017年 34卷 321-334页

作者： Ghorbani, Babak Kowsary, Farshad Ebrahimi, Sasan Vijayaraghavan, Krishna Simon Fraser Univ Sch Mechatron Syst Engn 250-13450 102 Ave Surrey BC V3T 0A3 Canada Univ Tehran Mech Engn Dept Tehran Iran

In this paper, the feasibility of a solar absorption refrigeration system to be powered by a latent heat storage (LHS) unit is investigated for a representative building. A single effect absorption chiller, utilizing Li-Br and water as working fluids is thermodynamically simulated. Then, the simulation of the latent heat storage unit is performed by applying finite difference method and the results were validated by the researches in the literature. Then, the geometry of a phase change material (PCM) based LHS system was optimized using multi-objective genetic algorithm for simultaneously minimizing the charging time, and maximizing the discharging time. Since the paper considers conflicting objectives, a Pareto front is presented that can be used for obtaining the optimum geometry according to the environmental conditions and working hours of the absorption system. As an illustrative example, the designed heat storage system was shown to be able to drive the 72 kW generator of an absorption system, for at least 10 h of operation in the discharging mode with the absence of sunlight. Therefore, it is possible to run absorption chillers under low-load operation conditions using the solar energy if the appropriate storage unit, such as what is introduced here, is used.

关键词： Single effect absorption system Li-Br and water Latent heat storage multi-objective genetic algorithm Optimization

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Detection and classification of cardiovascular abnormalities using FFT based multi-objective genetic algorithm

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BIOTECHNOLOGY & BIOTECHNOLOGICAL EQUIPMENT 2018年第1期32卷 183-193页

作者： Prasad, B. V. P. Parthasarathy, Velusamy Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala E Dept Elect & Commun Engn Madras Tamil Nadu India

Signal processing and data analysis are widely used methods in a biomedical research. In recent years, detection of cardiovascular abnormalities in patients can be achieved by using electrocardiogram (ECG) recording. In this paper, a fuzzy-based multi-objective algorithm using Fast Fourier Transform (FFT) is proposed. Initially, an effective FFT is used to extract the feature points in ECG signals, such as PQRST wave's amplitude and wave function and then the proposed multi-objective genetic algorithm is used to classify the abnormality of heart patient. Basically, the ECG behaviour depends on various factors such as age, physical condition of patients and the surrounding environment. The efficient detection of abnormalities (e.g. arrhythmia and myocardial abstraction) can be achieved by initializing the above-mentioned factors and maintaining a database containing previously attributed signals, such MIT-BIH arrhythmia. The present study provides efficiency of around 98.7% in detection of abnormalities in patients.

关键词： Fast Fourier Transform (FFT) cardiovascular abnormalities electrocardiogram (ECG) multi-objective genetic algorithm abnormalities

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Vibration Analysis of Switched Reluctance Motor Based on multi-objective genetic algorithm

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第2期18卷 1003-1011页

作者： Huang, Xiaocun Rao, Yingying Jing, Libing Cangzhou Normal Univ Coll Phys & Informat Engn 16 Guofeng South Ave Cangzhou Hebei Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Daxue Rd 8 Yichang Hubei Peoples R China

The vibration and noise caused by radial electromagnetic force hinder the development of switched reluctance motor (SRM). A structure with auxiliary slots in the stator teeth and rotor teeth of SRM is proposed in this paper. The radial force density and average torque are optimized by multi-objective genetic algorithm, and the optimal structural parameters of the motor are determined. The modal analysis and harmonic response analysis of the stator are carried out by using Workbench finite element software and compared with the conventional SRM. The results show that the radial force density is reduced by 42.19%, which verifies that opening auxiliary slots in stator teeth and rotor teeth is conducive to reducing the vibration of SRM.

关键词： Switched reluctance motor multi-objective genetic algorithm Modal analysis Harmonic response analysis

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