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Efficient Seizure Prediction and EEG Channel Selection Based on Multi-Objective Optimization

IEEE ACCESS 2023年 11卷 54112-54121页

作者： Jana, Ranjan Mukherjee, Imon Indian Inst Informat Technol Kalyani Dept CSE Kalyani 741235 West Bengal India RCC Inst Informat Technol Dept IT Kolkata 700015 India

Epileptic seizures are unpredictable events due to sudden abnormal electrical activities in the brain of epilepsy patients. A seizure can be predicted by analyzing the EEG signals to prevent unwanted life risks. The goal of this paper is to implement a method that will apply to design a lightweight, wearable, and efficient seizure prediction device. The proposed method will satisfy two objectives. The first objective is relevant feature extraction for the classification of EEG signals with excellent accuracy. The second objective is the use of fewer EEG channels. In this paper, one 1D-CNN is applied for feature extraction and classification of raw EEG signals for early prediction of seizure events. The 1D-CNN is faster compared to 2D-CNN, which uses fewer trainable parameters. Hence, it is suitable to implement a low-power energy-efficient seizure prediction device. In this paper, the nsga-ii algorithm is applied to get the optimum set of EEG channels for seizure prediction. The nsga-ii algorithm identifies a set of three EEG channels from twenty-two channels as the optimum channel set. The proposed method optimizes the EEG channels from 22 to 3, i.e., 86.36% channel reduction. It provides the classification accuracy, sensitivity, and specificity of 0.9651, 0.9655, and 0.9647, respectively. The proposed method is better than the state-of-the-art works under the condition of using three channels. The proposed method provides excellent performance using only three EEG channels, which will be applicable to design a lightweight, low-power, and wearable seizure prediction device.

关键词： Channel selection EEG signals multi-objective optimization nsga-ii algorithm seizure prediction 1D-CNN

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On the combined Brayton-Kalina cycle with PEM hydrogen production: An exergoeconomic analysis and multi-objective optimization with LINMAP decision maker

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年第PartA期52卷 289-304页

作者： Irani, Aida Sadri Fattahi, Abolfazl Univ Kashan Dept Mech Engn Kashan Iran

Energy recovery and hydrogen production are essential in the current energy horizon of the globe. Applying the waste thermal energy and producing clean fuels in the powergenerating cycles by keeping a sustainable view are the main goals of the current study. A combined Brayton-Kalina cycle accompanied by a PEM hydrogen production unit is studied using thermodynamic, exergetic, and economic evaluations. An external source is applied to supply the required heat for the closed Brayton cycle and the waste thermal energy is fed into the Kalina cycle. The Brayton cycle destructs more exergy than the Kalina cycle, respectively by the sharing value of 58% and 40%. The Brayton cycle shows the highest investment cost rate and the Kalina sets in the next rank. The PEM unit needs about 1% share of the total investment cost rate. A multi-objective optimization using nsga-ii algorithm is conducted to find the best operating conditions, considering the energy and exergy efficiency as well as investment cost rate function, as the objectives. The optimization makes an increase of 6% and 3% respectively in the total energy and exergy efficiency compared to the base working conditions, while it raises the investment cost rate by about 15%.(c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Brayton cycle Kalina cycle Exergoeconomic analysis PEM hydrogen Producer nsga-ii algorithm Cost rate

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Route planning for electric vehicles

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第7期16卷 875-889页

作者： Ben Abbes, Sirine Rejeb, Lilia Baati, Lasaad Univ Tunis Inst Super Gest Tunis ISG Tunis SMART Lab Tunis Tunisia

This work addresses the multi-objective route planning and charging problem for Battery Electric Vehicles (BEVs). The proposed solution is based on the nsga-ii algorithm to derive the Pareto-optimal set of eco-routes with the minimum travel and charging time, distance, energy consumption and charging costs while complying with the constraints related to the battery State of Charge (SoC) and the status of charging stations. Influencing factors, such as, vehicle and battery parameters, weather conditions, driver behaviour, road grade, Time Of Use (TOU) electricity cost, and Charging Stations (CS) status and type, are taken into account. The final results of the proposed method are compared with the well-established simulator SUMO.

关键词： BEVs battery powered vehicles battery parameters energy consumption electric vehicle charging Use electricity cost charging costs Charging Stations status multiobjective route planning Pareto optimisation eco-routes minimum travel nsga-ii algorithm weather conditions Battery Electric Vehicles Pareto-optimal set charging problem charging time genetic algorithms

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A novel meta-heuristic approach to solve fuzzy multi-objective straight and U-shaped assembly line balancing problems

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SOFT COMPUTING 2019年第17期23卷 8217-8245页

作者： Babazadeh, Hossein Javadian, Nikbakhsh Univ Sci & Technol Dept Ind Engn Tehran Iran Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran

The consideration of this study is devoted to deal with the straight and U-shaped assembly line balancing problems (ALBPs). The ALBP involves allocation of required tasks to a set of workstations, so that objective functions being optimized are subjected to set of constraint. While many efforts have been dedicated in the literature to develop deterministic model of the assembly line, the attention is not considerably paid to those in uncertain circumstances. In this paper, along with proposing a novel fuzzy model for ALBP, triangular fuzzy numbers are deployed with to respect vagueness and uncertainty subjected to the task processing times. For this purpose, two conflicting objectives are considered simultaneously with regard to set of constraints, so that the efficiency of the line has to be maximized. To solve the problem, a modified nsga-ii, which utilized a new repairing mechanism, is proposed in response to the need of appropriate method treating such complicated problems. The validity of the proposed model and algorithm is evaluated and proved though a benchmark test problem. The obtained results reveal that in contrast to benchmark that applied an exact solution procedure, the proposed algorithm is capable of delivering the astonishing solutions in a more effective procedure. Along with the use of nsga-ii, in this study, three well-known meta-heuristic algorithms, namely PESA-ii, NSACO and NPGA-ii, are also employed for solving the problem in order to evaluate the effectiveness of the proposed algorithm, so that the results demonstrate the high performance for the nsga-ii over them. Finally, in light of the obtained results, this study offers an efficient framework enabling the decision maker to handle uncertainty in ALBPs along with the use of an efficient algorithm to solve them.

关键词： Multi-objective optimization Assembly line balancing Fuzzy programming nsga-ii algorithm Repairing mechanism

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Optimization of falling film thermosyphons bundle arrangement for large-scale cooling applications by genetic algorithm

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APPLIED THERMAL ENGINEERING 2020年 169卷 114892-000页

作者： Zhong, Wei Cao, Xiaoling Yuan, Yanping Southwest Jiaotong Univ Sch Mech Engn Chengdu 610031 Peoples R China

Two-phase traditional thermosyphons (TTS) are passive heat exchangers with low thermal resistance for heat transfer. An advanced thermosyphon system named falling film thermosyphon (FFTS) is developed and introduced in this paper, which eliminates several limits of TTS and improves heat transfer performance. FFTS applications are preferred for large-scale heat transfer applications. In this work, a tube bank of FFTS modules is integrated into a power plant to condense water vapor of the flue gas. Axial- and cross- flow are both analyzed with inline and staggered arrangements. The numerical simulation of vapor condensation in the flue gas is developed, and the results are compared to previously published experimental data. The accuracy of model is validated. The Non-dominated Sorting Genetic algorithm, version 2 (nsga-ii) is implemented to improve the thermal performance with low material consumption and pressure drop for tube banks. Several parameters of the configuration are optimized. As a result, smaller diameter tubes with longer length can gain better heat transfer performance, however, resulting in a higher pressure drop. The optimized arrangements can improve 60-70% condensation rate and reduce up to 80% material consumption with allowable pressure loss compared to a baseline geometry.

关键词： Thermosyphon Heat transfer Condensation nsga-ii algorithm Tube bank

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Multi-Objective Optimization of Integrated Surface and Groundwater Resources Under the Clean Development Mechanism

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WATER RESOURCES MANAGEMENT 2021年第8期35卷 2685-2704页

作者： Majedi, Hamidreza Fathian, Hossein Nikbakht-Shahbazi, Alireza Zohrabi, Narges Hassani, Fatemeh Islamic Azad Univ Ahvaz Branch Dept Water Resources Engn Ahvaz Iran Shirin Ab Zamin Consulting Engineers Co Ahvaz Iran

Acquiring sustainable water resources for water-based development of countries is the experts concern in this field, who seek to follow the clean development mechanism (CDM) regulations and overcome water crisis through integrated water resources management (IWRM). The Great Karun River basin is one of the major basins in the Middle East. This basin, containing six of the largest reservoir dams with a cumulative power plant capacity of more than 10,500 MW generates about 93% of hydropower of Iran. The water balance of the aquifer in the study area was simulated using MODFLOW model while water resources and surface water reserves were simulated by the water evaluation and planning (WEAP) model. A separate simulation was performed with each of two models and the results of two models were coupled using a link file. The multi-objective function optimization process including the maximized supply of demands and hydropower and the minimized aquifer drawdown was completed using non-dominated sorting genetic algorithm (nsga-ii). All effective system components, such as inter-basin water transfer, integrated use of water resources, variation of irrigation network efficiencies, and the effect of water shortage were studied and analyzed under the targeted scenarios. Finally, the best scenario, which was capable to supply the future needs until time horizon of 2040 was planned for the basin considering minimization of aquifer drawdown and optimal generation of hydropower resulting in a maximum decrease in emission of greenhouse gases.

关键词： Multi-objective optimization Clean development mechanism Greenhouse gas Hydropower nsga-ii algorithm

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Multi-objective optimization of thermo-hydraulic behavior of heat exchanger with v-cut twisted tape in axial and radial direction using nsga-ii

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2023年第4期45卷 13057-13076页

作者： Singh, Sanjay Kumar Kacker, Ruchin Gautam, Satyam Shivam Tamang, Santosh Kumar Sagar Inst Sci & Technol Dept Mech Engn Bhopal India NERIST Dept Mech Engn Itanagar India Sagar Inst Sci & Technol Dept Mech Engn Bhopal 462036 Madhya Pradesh India

In pursuit of optimizing the thermo-hydraulic behavior of a heat exchanger, this study employs twisted tape inserts, a well-known method for enhancing heat transfer rates in heat exchange devices compared to plain tubes. Experiments involving v-cut twisted tapes with v-angles of 15 degrees, 30 degrees, and 45 degrees in both axial and radial directions were conducted within a double pipe heat exchanger, encompassing a Reynolds number range from 5500 to 10,000, with water as the flowing medium. As part of the modeling approach, response surface methodology (RSM) was harnessed to construct mathematical models for the heat transfer rate, quantified as the Nusselt number, and the friction factor. This modeling accounted for independent variables including Reynolds number, Prandtl number, axial angle, and radial angle. The RSM models demonstrated high statistical significance and reliability, yielding an R-squared value exceeding 97%, with the linear terms of Reynolds number and cut angles identified as the most influential factors. To attain optimization, a multi-objective approach was adopted, employing the nsga-ii algorithm. This algorithm efficiently explored the design parameter space, seeking the optimal combination that maximizes heat transfer rate and minimizes the friction factor simultaneously. Quantitative results from the experimentation revealed that, at a Reynolds number of 10,000, the Nusselt number achieved its peak value of 96.51. Conversely, the highest friction factor (0.0582) and performance evaluation criteria (PEC) of 1.65 emerged at a Reynolds number of 5500, specifically when employing a 45-degree radial v-cut angle. Notably, this configuration led to substantial enhancements: the Nusselt number increased by 98.7%, the friction factor by 38.9%, and the PEC by 39.4% compared to a plain tube. These findings underscore both the effectiveness of the nsga-ii algorithm in optimizing heat exchanger designs and the valuable insights gained into the influe

关键词： Nusselt number friction factor twisted tape axial and radial v-cut RSM nsga-ii algorithm

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Optimum number of cascade cells for multilevel inverter considering redundancy strategies based on cost and reliability optimization

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IET GENERATION TRANSMISSION & DISTRIBUTION 2023年第19期17卷 4423-4436页

作者： Azimi, Maede Asadi, Mehdi Arak Univ Technol Dept Elect Engn Arak Iran

This paper proposes an economical reliability-oriented solution to determine the optimal number of cascade cells and redundancies for STATCOM using a Non-Dominated Sorting Genetic (nsga-ii) algorithm based on different redundancy configuration schemes. A multi-objective optimization framework is presented, to minimize the total cost and maximize its reliability index by considering power quality issues. In the presented model, a new cost modelling is introduced considering the cost of inductor loss. The multilevel cascade topology with staircase modulation strategy is also taken into account. The effectiveness of the proposed optimization framework is validated by the nsga-ii algorithm compared to the results of goal attainment and goal programming as decomposition single-objective optimization methods. The results verify that the proposed multi-objective optimization framework could be useful in the optimal selection of high-voltage STATCOM levels in the presence of redundancies while ensuring the required level of reliability at the minimum cost. Also, the presented nsga-ii optimization algorithm is applicable to maintain both objective functions at an acceptable value. The optimal number of multilevel-based STATCOM is determined based on a novel multi-objective optimization scheme aiming to maximize reliability and to minimize total cost considering power quality issues. The current harmonic effects on the loss costs are taken into account to develop a new cost modelling scheme and to evaluate inductor loss costs impacts on the total cost in the presence of hot and cold redundancies. The effectiveness of the proposed optimization scheme is evaluated based on the nsga-ii algorithm and different decomposition optimization algorithms including goal attainment and goal programming and discussed the proposed optimization framework with more detailed ***

关键词： multi-objective optimization nsga-ii algorithm redundancy reliability STATCOM

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Multi-objective optimization of an endoreversible closed Atkinson cycle

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JOURNAL OF NON-EQUILIBRIUM THERMODYNAMICS 2024年第1期49卷 73-88页

作者： Gong, Zheng Ge, Yanlin Chen, Lingen Feng, Huijun Wuhan Inst Technol Inst Thermal Sci & Power Engn Wuhan 430205 Peoples R China Wuhan Inst Technol Sch Mech & Elect Engn Wuhan 430205 Peoples R China Res Ctr Green Chem Equipment Hubei Prov Engn Technol Wuhan 430205 Peoples R China

Based on finite-time-thermodynamic theory and the model established in previous literature, the multi-objective optimization analysis for an endoreversible closed Atkinson cycle is conducted through using the nsga-ii algorithm. With the final state point temperature (T-2) of cycle compression process as the optimization variable and the thermal efficiency (eta), the dimensionless efficient power (E-P), the dimensionless ecological function (E) and the dimensionless power (P) as the optimization objectives, the influences of T-2 on the four optimization objectives are analyzed, multi-objective optimization analyses of single-, two-, three-and four objective are conducted, and the optimal cycle optimization objective combination is chosen by using three decision-making methods which include LINMAP, TOPSIS, and Shannon Entropy. The result shows that when four-objective optimization is conducted, with the ascent of T-2, P descends, eta ascends, both E and E-P firstly ascend and then descend. In this situation, the deviation index is the smallest and equals to 0.2657 under the decision-making method of Shannon Entropy, so its optimization result is the optimal. The multi-objective optimization results are able to provide certain guidelines for the design of practical closed Atkinson cycle heat engine.

关键词： finite time thermodynamics closed Atkinson cycle multi-objective optimization nsga-ii algorithm ecological function efficient power

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Multi-objective lightweight design of automotive battery pack box for crashworthiness

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INTERNATIONAL JOURNAL OF CRASHWORTHINESS 2024年第2期29卷 292-307页

作者： Wang, Hui Wang, Zhaohui Fan, Yiwei Gao, Quanjie Wang, Hongxia Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Minist Educ Wuhan Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Peoples R China Hubei Longzhong Lab Xiangyang Hubei Peoples R China Hubei Univ Automot Technol Coll Mech Engn Shiyan Hubei Peoples R China

To study an efficient lightweight method of electric vehicle power packs, the paper proposes that a hybrid method is combined with the modified Genetic algorithm (nsga-ii), the contribution analysis method and the TOPSIS method for improving the battery pack enclosure (BPE) crashworthiness and reducing the structural mass. First, the finite element model of BPE and the crushing crashworthiness model were established and effectively verified by constrained modal analysis and crushing tests. Next, the initially selected optimized components were screened with the contribution analysis method to identify the final optimized components with thickness as the design variable. Also, the battery pack structure values at a design point with the Latin hypercube sampling are obtained. Moreover, the response surface (RSM) agent model was used to construct a relationship between optimization indicators and the design variables. Based on that, this paper carried out the multi-objective optimization design of nsga-ii algorithm and obtained the optimal compromise solution by TOPSIS method. And finally, by numerical simulation, the optimization results were verified and compared with the initially designed BPE. The results showed that the optimized battery pack components reduced the total weight by 4.31% and the crushing deformation of the box by 5.97%.These results contribute to the lightweight and crash-resistant BPE design with excellent performance.

关键词： Battery pack enclosure crashworthiness nsga-ii algorithm multi-objective lightweight design

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