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arXiv 2024年

作者： Nasir, Jamal Abdul Guan, Jingcheng Jee, Woongkyu Woodley, Scott M. Sokol, Alexey A.C. Catlow, Richard A. Elena, Alin-Marin Department of Chemistry Kathleen Lonsdale Materials Chemistry University College London 20 Gordon Street LondonWC1H 0AJ United Kingdom UK Catalysis Hub Research Complex at Harwell Rutherford Appleton Laboratory R92 Harwell OxfordshireOX11 0FA United Kingdom School of Chemistry Cardiff University Park Place CardiffCF10 3AT United Kingdom STFC Scientific Computing Department Daresbury Laboratory Keckwick Lane Daresbury WarringtonWA4 4AD United Kingdom

Silica polymorphs and zeolites are fundamental to a wide range of industrial applications owing to their diverse structural characteristics, thermodynamic and mechanical stability under varying conditions and due to their geological importance. Computational modelling has played a crucial role in understanding the relationship between the structure and functionality of silicas and silicates including zeolites. In this study, we apply the MACE-MP-0 machine learnt interatomic potentials (ML-IP) to model the framework energies of siliceous zeolites and examine the phase transitions of silica and ZSM-5 polymorphs under high-pressure conditions. The results reproduce the known metastability of siliceous zeolites relative to α-quartz, with energy differences between microporous and dense phases calculated by MACE-MP-0 medium ML-IP and density functional theory (DFT) methods closely aligning with experimental calorimetric data. The high-pressure simulations reveal distinct compression behaviour in the quartz, coesite, and stishovite polymorphs of silica, with coesite and stishovite showing increased stability at elevated pressures in line with experimental data. The calculated phase transition pressures from quartz to coesite (~3.5 GPa) and coesite to stishovite (~9 GPa) are close to experimental findings, demonstrating the reliability of MACE ML-IP in modelling the structural and energetic properties of silica polymorphs. © 2024, CC BY.

关键词： High pressure effects in solids

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Traffic Signal optimization using Cultural Algorithm 4

Traffic Signal Optimization using Cultural Algorithm

引用

4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022

作者： Tan, Min Keng Vun, Hon Yang Ee Chuo, Helen Sin Lim, Kit Guan Yang, Soo Siang Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Traffic congestion is one of the major issues in most cities. Over time, traffic congestion is increasing due to the increasing number of road users. The conventional non-adaptive traffic signal control strategy is inadequate to optimize the traffic flow during peak hours. Thus, this paper explores the feasibility of optimizing traffic signal timing using cultural algorithm to minimize the traffic queue length at every intersection within a network. Since the traffic congestion can be propagated from upstream intersection to downstream intersection, the proposed algorithm will consider the traffic condition at neighboring intersections when computing the optimum traffic signal timing. The performance of the proposed algorithm is simulated and compared with the conventional fixed timing system. The results show the proposed cultural algorithm is able to improve the traffic flow by 20 %. © 2022 IEEE.

关键词： Traffic congestion

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An IGD+ Indicator-Based Metric for Interactive Evolutionary Multi-Objective optimization Algorithms

An IGD+ Indicator-Based Metric for Interactive Evolutionary ...

引用

Chinese Automation Congress (CAC)

作者： Hao Tian Fei Li Baiyu Zhou Yujie Yang Xun Huang School of Electrical and Information Engineering Anhui University of Technology Maanshan Anhui Province Engineering Laboratory of Intelligent Demolition Equipment Anhui University of Technology Maanshan Anhui Province Key Laboratory of Special Heavy Load Robot Anhui University of Technology Maanshan

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Interactive evolutionary multi-objective optimization algorithms have received widespread research. The goal of these algorithms is to iteratively involve decision makers(DM) in the solution process, by providing preference information, the solution is guided to regions of interest. However, most indicators are designed to assess how well algorithms approximate the entire Pareto optimal front. In order to assess the quality of the preferred solution sets obtained by interactive algorithms, this paper introduces a novel performance indicator based on the modified inverted generational distance (IGD + ). The indicator is examined using interactive evolutionary methods and demonstrating its capability to evaluate the performance of interactive algorithms.

关键词： Measurement Automation Pareto optimization Approximation algorithms optimization

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Advances in Sn-based oxide catalysts for the electroreduction of CO_(2) to formate

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Green Carbon 2024年第2期2卷 131-148页

作者： Xiaoyue Tu Xiangjian Liu Yu Zhang Jiawei Zhu Heqing Jiang Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of SciencesQingdao 266101China Shandong Energy Institute Qingdao 266101China Qingdao New Energy Shandong Laboratory Qingdao 266101China University of Chinese Academy of Sciences Beijing 100049China

The excessive consumption of fossil fuels increases carbon dioxide(CO_(2))emissions,and the consequent greenhouse effect resulting from higher levels of this gas in the atmosphere has a significant impact on the environment and *** has necessitated the development of environmentally friendly and efficient methods for CO_(2)*** carbon dioxide electroreduction reaction(CO_(2)RR),which is driven by electricity generated by renewable energy sources(e.g.,wind and solar)to convert CO_(2)into value-added fuels or chemicals,is regarded as a promising prospective path toward carbon *** the various products,formate,with its relatively simple preparation process,has broad application prospects,and can be used as fuel,hydrogen storage material,and raw material for downstream ***-based oxide electrocatalysts have the advantages of being inexpensive and *** addition,these catalysts offer high product selectivity and are regarded as promising catalysts for the electrochemical reduction of CO_(2)to *** this review,we first clarify the reaction mechanisms and factors that influence the reduction of CO_(2)to formate,and then provide some examples of technologies that could be used to study the evolution of catalysts during the *** particular,we focus on traditional Sn-based oxides(SnO_(2))and novel Sn-based perovskite oxides that have been developed for use in the field of CO_(2)RR in recent years by considering their synthesis,catalytic performance,optimization strategies,and intrinsic ***,the current challenges and opportunities for Sn-based oxide electrocatalysts are *** perspectives and latest trends presented in this review are expected to inspire researchers to contribute more efforts toward comprehensively optimizing the performance of the CO_(2)RR to produce formate.

关键词： CO_(2)electroreduction Sn-based oxides Formate Perovskite

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A Survey on Intelligent optimization Approaches to Boiler Combustion optimization

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CAAI Artificial Intelligence Research 2023年第1期2卷 16-31页

作者： Jing Liang Hao Guo Ke Chen Kunjie Yu Caitong Yue Yunpeng Ma School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Intelligent Agricultural Power Equipment Luoyang 471000China School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453000China School of Information Engineering Tianjin University of CommerceTianjin 300134China

This paper reviews the researches on boiler combustion optimization,which is an important direction in the field of energy saving and emission *** methods have been used to deal with boiler combustion optimization,among which evolutionary computing(EC)techniques have recently gained much ***,the existing researches are not sufficiently focused and have not been summarized *** has led to slow progress of research on boiler combustion optimization and has obstacles in the *** paper introduces a comprehensive survey of the works of intelligent optimization algorithms in boiler combustion optimization and summarizes the contributions of different optimization ***,this paper discusses new research challenges and outlines future research directions,which can guide boiler combustion optimization to improve energy efficiency and reduce pollutant emission concentrations.

关键词： boiler combustion optimization circulating fluidized bed boiler environmental protection computational intelligence intelligent optimization algorithm

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Unified Enhancement of the Generalization and Robustness of Language Models via Bi-Stage optimization

arXiv

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arXiv 2025年

作者： Sun, Yudao Yin, Juan Zhao, Juan Zhang, Fan Liu, Yongheng Chen, Hongji Department of New Networks Peng Cheng Laboratory Shenzhen518055 China Department of Industrial Systems Engineering and Management National University of Singapore Singapore117576 Singapore School of Data Science and Artificial Intelligence Chang’an University Shaanxi 710064 China

Neural network language models (LMs) are confronted with significant challenges in generalization and robustness. Currently, many studies focus on improving either generalization or robustness in isolation, without methods addressing both aspects simultaneously, which presents a significant challenge in developing LMs that are both robust and generalized. In this paper, we propose a bi-stage optimization framework to uniformly enhance both the generalization and robustness of LMs, termed UEGR. Specifically, during the forward propagation stage, we enrich the output probability distributions of adversarial samples by adaptive dropout to generate diverse sub-models, and incorporate JS-divergence and adversarial losses of these output distributions to reinforce output stability. During backward propagation stage, we compute parameter saliency scores and selectively update only the most critical parameters to minimize unnecessary deviations and consolidate the model’s resilience. Theoretical analysis shows that our framework includes gradient regularization to limit the model’s sensitivity to input perturbations and selective parameter updates to flatten the loss landscape, thus improving both generalization and robustness. The experimental results show that our method significantly improves the generalization and robustness of LMs compared to other existing methods across 13 publicly available language datasets, achieving state-of-the-art (SOTA) performance. © 2025, CC BY-NC-ND.

关键词： Sensitivity analysis

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Adam-family methods for Nonsmooth optimization with Convergence Guarantees

arXiv

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arXiv 2023年

作者： Xiao, Nachuan Hu, Xiaoyin Liu, Xin Toh, Kim-Chuan Institute of Operations Research and Analytics National University of Singapore 3 Research Link Singapore117602 Singapore School of Computer and Computing Science Hangzhou City University Hangzhou310015 China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Mathematics Institute of Operations Research and Analytics National University of Singapore 10 Lower Kent Ridge Road Singapore119076 Singapore

In this paper, we present a comprehensive study on the convergence properties of Adam-family methods for nonsmooth optimization, especially in the training of nonsmooth neural networks. We introduce a novel two-timescale framework that adopts a two-timescale updating scheme, and prove its convergence properties under mild assumptions. Our proposed framework encompasses various popular Adam-family methods, providing convergence guarantees for these methods in training nonsmooth neural networks. Furthermore, we develop stochastic subgradient methods that incorporate gradient clipping techniques for training nonsmooth neural networks with heavy-tailed noise. Through our framework, we show that our proposed methods converge even when the evaluation noises are only assumed to be integrable. Extensive numerical experiments demonstrate the high efficiency and robustness of our proposed methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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High-Quality-Factor Superconducting Cavities in Tesla-Scale Magnetic Fields for Dark-Matter Searches

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Physical Review Applied 2023年第3期20卷 034004-034004页

作者： S. Posen M. Checchin O.S. Melnychuk T. Ring I. Gonin T. Khabiboulline Fermi National Accelerator Laboratory Batavia Illinois 60510 USA

In dark-matter searches using axion haloscopes, the search sensitivity depends on the quality factors (Q0) of radio-frequency cavities immersed in multitesla magnetic fields. Increasing Q0 would increase the scan rate through the parameter space of interest. Researchers developing superconducting radio-frequency cavities for particle accelerators have developed methods for obtaining extremely high Q0 of approximately 1011 in microteslascale magnetic fields. In this paper, we describe efforts to develop high-Q cavities made from Nb3Sn films using a technique developed for particle-accelerator cavities. Geometry optimization for this application is explored, and two cavities are tested: an existing particle-accelerator-style cavity and a geometry developed and fabricated for use in high fields. A quality factor of (5.3±0.3)×105 is obtained at 3.9 GHz and 6 T at 4.2 K.

关键词： High magnetic fields Superconducting RF Axions Type-II superconductors Dark matter detectors

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Energy-Efficient Ant Colony Based LEACH Routing Algorithm in Wireless Sensor Network 4

Energy-Efficient Ant Colony Based LEACH Routing Algorithm in...

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4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022

作者： Abd Latif, Muhammad Zahir Lim, Kit Guan Tan, Min Keng Ee Chuo, Helen Sin Wang, Tienlei Kin Teo, Kenneth Tze Modelling Simulation & Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia Wuyi University Department of Intelligent Manufacturing Jiangmen China

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Wireless sensor network (WSN) is a network consist of multiple sensor nodes which sense and transmit data to a base station for data collection. Since the nodes in WSN are battery powered devices and nodes loss energy mostly due to transmission, an energy efficient routing protocol is needed to reduce the nodes energy consumption and prolong the network lifetime. However, existing routing protocols produce some drawbacks such as selection of cluster head with low residual energy and formation of different sizes of cluster which leads to uneven energy consumption among the nodes. Therefore, an Ant Colony optimization based Low Energy Adaptive Clustering Hierarchy (LEACH-ACO) protocol for energy efficient transmission in WSN is proposed in this paper. This research aims to develop a routing protocol that utilize the existing LEACH routing protocol to improve the performance of WSN and prolong the lifetime of the network. The results showed that LEACH-ACO protocol outperformed Direct Transmission (DT) and LEACH protocol in terms of network lifetime, energy consumption and energy per transmission. © 2022 IEEE.

关键词： Ant colony optimization

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optimization strategies for outdoor thermal comfort at urban core transportation hub in summer–A case of Turpan Station, China

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Building and Environment 2025年 279卷

作者： Su, Yuan Wang, Yongxin Huang, Ziyang Peng, Tiantian Han, Yu Wang, Wanjiang Meng, Qinglin Saimaiti, Adili School of Architecture and Fine Art Dalian University of Technology Dalian116024 China School of Architecture and Engineering Xinjiang University Xinjiang Urumqi830049 China School of Architecture South China University of Technology State Key Laboratory of Subtropical Building Science Guangzhou510640 China

As global warming escalates, high-intensity heat waves are increasingly common, raising concerns about their impact on environmental systems and public health. This article focuses on Turpan City, known for having the highest summer temperatures in China, emphasizing its largest transportation hub, Turpan North Station. The study employs field research and data measurement to analyze the local summer climate conditions. Additionally, simulation methods were utilized to assess the spatial and temporal changes in the area's thermal environment. The research also evaluates six design scenes featuring various configurations of blue-green infrastructure, using the Universal Thermal Climate Index (UTCI) for evaluation. The results show that the average radiation temperature (Tmrt) becomes the primary factor influencing the UTCI. The incorporation of tall trees in varying proportions leads to a substantial reduction in Tmrt, with the greatest decrease amounting to 6.79°C. Furthermore, through the strategic allocation of urban blue-green infrastructure, the UTCI values are decreased by 1.33°C relative to the actual situation and by 1.73°C when compared to simulations lacking blue-green infrastructure. Moreover, the duration of "extreme heat stress" is reduced by a duration of 2 hours. This study also suggests targeted optimization and improvement strategies based on the characteristics of various functional zones surrounding transportation stations. Overall, it provides a robust theoretical foundation and practical guidance for the scientific planning and effective arrangement of the outdoor thermal environment in rail transit buildings in dry and hot regions. © 2025 Elsevier Ltd

关键词： Urban transportation

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