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combination algorithm for curve fitting of XPS data and detection

Jinshu Xuebao/Acta Metallurgica Sinica 1996年第2期32卷 224-224页

作者： Gong, Yandong Institute of Metal Research Chinese Academy of Sciences Shenyang 110015 China

A new line shape was chosen for curve fitting of XPS (X-ray photoelectron spectroscopy) data. In general, the GLP(Gauss-Lorentz product function) or GLS(Gauss-Lorentz sum function) was used as the line shape of XPS, but they are not strict because the true line shape is a convolution of many comments. A convoluted line shape is chosen in fitting procedure. The new algorithm is called 'combination algorithm'. A detection was taken with Cu 3p spectrum and O 1s spectra of Fe-Mn-Al alloy. It is shown that the combination algorithm is more effective for the process of XPS data than GLP and GLS.

关键词： combination algorithm Line shape of XPS XPS

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Study on Seismic Magnitude Prediction Based on combination algorithm

Study on Seismic Magnitude Prediction Based on Combination A...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Wan-zhen Zhou Jing-sen Kan Shuo Sun the School of Information Science & Engineering Hebei University of Science and Technology the School of Information Science & Engineering Shandong University

Earthquake as a kind of natural disaster,it has a great destruction,but the magnitude of earthquake is closely related to the latitude,longitude and the depth of *** is very important to realize the magnitude prediction by data *** order to reduce the damage degree of earthquake to human's life and enhance the prediction ability of magnitude at different sites and depth of source,the support vector machine(SVM) and neural network algorithm are used to construct the magnitude prediction model based on existing seismic data,and the prediction of possible earthquake magnitude at different locations and focal depth is realized based on combination algorithm of support vector machine and neural *** results shows that the predictive ability of combination algorithm is better than using traditional SVM or neural network obviously,and have large extent overcome the disadvantage of support vector machine in solving multi-classification problems and bad selection of artificial neural network parameters easily lead to over-fitting or under-fitting and other disadvantages.

关键词： Data mining combination algorithm support vector machine neural network magnitude prediction

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Secure combination of Untrusted Time Information Based on Optimized Dempster-Shafer Theory

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Li, Yang Luo, Yujie Fang, Lujun Zhang, Yichen Huang, Wei Sun, Ao Zhang, Shuai Zhang, Tao Zhou, Chuang Ma, Li Yang, Jie Wang, Heng Pan, Yan Shao, Yun Chen, Xing Chen, Ziyang Yu, Song Luo, Bin Guo, Hong Xu, Bingjie Inst Southwestern Commun Natl Key Lab Secur Commun Chengdu 610041 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China Peking Univ Sch Elect State Key Lab Adv Opt Commun Syst & Networks Beijing 100871 Peoples R China Peking Univ Ctr Quantum Informat Technol Beijing 100871 Peoples R China

Secure precision time synchronization is important for applications of cyber-physical systems (CPSs). However, several attacks, especially the time delay attack (TDA), deteriorate the performance of the time synchronization system seriously. The multiple paths scheme is thought as an effective security countermeasure to decrease the influence of TDA. However, the effective secure combination algorithm is still missed for precision time synchronization. In this article, a secure combination algorithm based on the Dempster-Shafer (D-S) theory is proposed for the multiple paths method. Special optimizations are done for the combination algorithm to solve the potential problems due to untrusted evidence. Theoretical simulation shows that the proposed algorithm works much better than the fault-tolerant algorithm (FTA) and the attack detection method based on a single path. An experimental demonstration proves the feasibility and superiority of the proposed algorithm, where the time stability with 27.97, 1.57, and 1.12 ps at average time 1, 10, and 100 s is achieved under TDAs and local clock jumps. The proposed algorithm can be used to improve the security and resilience of many important synchronization protocols, such as network time protocol (NTP), precision time protocol (PTP), and two-way fiber-optic time transfer (TWFTT).

关键词： Synchronization Clocks Security Main-secondary Mathematical models Delays Evidence theory Standards Time-frequency analysis Sun combination algorithm delay attack Dempster-Shafer (D-S) theory security time synchronization two-way fiber-optic time transfer (TWFTT)

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Three stage based reinforcement learning for combining multiple metaheuristic algorithms

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SWARM AND EVOLUTIONARY COMPUTATION 2025年 95卷

作者： Liu, Xiaotong Wang, Tianlei Zeng, Zhiqiang Tian, Ye Tong, Jun Wuyi Univ Sch Mech & Automat Engn Jiangmen 529020 Peoples R China Wuyi Univ Sch Elect & Informat Engn Jiangmen 529020 Peoples R China Dongguan Univ Technol Sch Mech Engn Dongguan 523808 Peoples R China Anhui Univ Sch Comp Sci & Technol Hefei 230601 Peoples R China Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2500 Australia Jiangmen Key Lab Kejie Semicond Bonding Technol & Jiangmen 529020 Peoples R China

Combined of metaheuristic algorithms can effectively improve the performance of algorithms by utilizing the characteristics of different metaheuristic algorithms, and the key is how to combine multiple metaheuristic algorithms. Reinforcement learning is one of the effective methods for combining multiple metaheuristic algorithms. However, designing a competitive reinforcement learning approach to achieve efficient collaboration among metaheuristic algorithms is a highly challenging task. Therefore, this study proposes a three-stage reinforcement learning for combining multiple metaheuristic algorithms (TSRL-CMM). TSRL-CMM is divided into three stages: the exploration stage, the stage with both exploration and exploitation, and the exploitation stage. On this basis, an adaptive action selection strategy and a reward function are designed. The proposed action selection strategy can adaptively select appropriate metaheuristic algorithms based on the state of the population, achieving a balance between exploration and exploitation. The proposed reward function can effectively guide the population to transition to the expected state based on the iteration stage and state transitions. To verify the effectiveness of TSRL-CMM, we evaluated it using the CEC2017 test suite, nine real-world engineering design problems and six power system optimization problems. TSRL-CMM was compared with 10 state-of-the-art metaheuristic algorithms, and experimental results showed that TSRL-CMM performed better than the compared algorithms in both artificial and real-world problems. Furthermore, TSRL-CMM was specifically compared with three CEC winner algorithms on the CEC 2017 benchmark test suite. The experimental results show that the proposed algorithm is highly competitive. The source code can be obtained from https://***/xtongliu/TSRL-CMM-code.

关键词： Reinforcement learning combination algorithm Metaheuristic algorithm Engineering optimization

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Research and application of the algorithm editing method for improving active noise control performance

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JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL 2025年

作者： Song, Haisheng Dong, Yahui Yang, Na Chen, Zhiyong Henan Inst Technol Sch Vehicle & Traff Engn Pingyuan Rd 699 Xinxiang 453002 Peoples R China Jilin Univ State Key Lab Automot Simulat & Control Changchun Peoples R China Shaanxi Heavy Duty Automobile Co LTD Inst Automot Engn R&D Xian Peoples R China

In the field of active noise control systems, combining multiple algorithms to improve equalization performance has generated notable interest. Nevertheless, the computation of threshold control parameters for algorithm switching during each iteration leads to a significant increase in computational complexity. Additionally, the frequent switching of algorithms poses challenges in fully leveraging the performance of individual algorithms. Therefore, this paper utilizes the film editing concept to introduce the algorithm Editing Method (AEM). AEM entails selecting appropriate algorithms based on distinctive iteration stages, followed by precise cutting and splicing according to the defined switching coefficient. Appropriate algorithms are implemented at specific iteration stages, eliminating the requirement for frequent algorithm switching during the iterative process. To substantiate the effectiveness of this approach, the FxLMS and Momentum-FxLMS algorithms serve as foundational components of AEM, enhancing convergence performance in an active noise control system. The results show a noteworthy enhancement in convergence speed and reduction of steady-state error, attained without a simultaneous escalation in computational complexity. Additionally, this study extends the application of AEM to improve the system's robustness against impulse signals. The simulations and tests results demonstrate the method's effectiveness, achieving a balance of optimized convergence speed, reduction in steady-state error, and minimized computational complexity.

关键词： Active noise control adaptive filter algorithm editing method combination algorithm

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Optimal operation of single unit in pumping station based on a combination of orthogonal experiment and 0-1 integer programming algorithm

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WATER SUPPLY 2022年第11期22卷 7905-7915页

作者： Wang, Shiwen Cheng, Jilin Zhu, Bowen Yangzhou Univ Coll Hydraul Sci & Engn Yangzhou 225009 Peoples R China Yangzhou Univ Inst Modern Rural Water Conservancy Yangzhou 225009 Peoples R China

The frequent start-stop scheme in the operation management of large pumping stations causes a series of problems, e.g., energy consumption and potential safety hazard. Therefore, we established a mathematical model for the optimal operation of a large-scale pumping station considering the start-stop loss of machine. The objectives of the optimization model included electricity charges for pumping station operation and the start-stop loss of pumping station. The blade angle and start-stop scheme were taken into account as the double decision variables, while the target water extraction (equality constraint), start-stop scheme and power were the constraint conditions. A combination of orthogonal experiment and 0-1 integer programming algorithm was proposed to exploring the optimal solution of the model. A real case of single-unit pump station in China was applied to prove the effectiveness of the algorithm. The results showed that the optimization efficiency of proposed algorithm was 4%-10% higher than that of genetic algorithm. Additionally, the maximum optimization benefit was obtained when the number of start-stop was less than 3 times during operation process. The proposed algorithm provided a reference for similar complex nonlinear models.

关键词： blade angle combination algorithm pump station single unit start-stop scheme test selection

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A combination-based machine learning algorithm estimating impacts of social, economic, and environmental on resident health-on China?s provincial panel data

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第PartA期123卷

作者： Wen, Li Pan, Wei Liao, Shujie Pan, Wulin Xu, Hui Hu, Cheng Renmin Univ China Sch Appl Econ Beijing 100872 Peoples R China Huazhong Univ Sci & Technol Tongji Hosp Tongji Med Coll Canc Biol Res CtrDept Obstet & Gynecol Wuhan 430030 Hubei Peoples R China Wuhan Univ Sch Econ & Management Wuhan 430072 Peoples R China Wuhan Univ Dong Fureng Inst Econ & Social Dev Wuhan 430072 Peoples R China

The factors influencing residents health have become complex and intertwined with the development of economy and society. Traditional research with a single factor on health will not provide an accurate picture of the situation. This paper collects data on economic, environmental and social factors to estimate their impact on regional health. Considering the data is multi-source and complex, this paper proposes a combined feature importance algorithm, which weighted the feature importance of RF, XGB and SOIL. The algorithm does not depend on the data and adaptively approximates the true results. The results show that economic factors have a significant and direct impact on health, environmental factors have a lag correlation with health level, and social factors have a more complicated effect on health. Finally, we provide policy suggestions for health on economic, environmental, and social development.

关键词： Residents health combination algorithm Feature importance

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EMD-based multi-algorithm combination model of variable weights for oil well production forecast

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ENERGY REPORTS 2022年 8卷 13389-13398页

作者： Cao, Yu Liu, Shanke Cao, Xiaopeng Liu, Xinyi Hu, Huifang Zhang, Tingting Yu, Lijun Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Sinopec Shengli Oilfield Explorat & Dev Res Inst Dongying 257015 Shandong Peoples R China Shanghai Jiao Tong Univ Coll Smart Energy 665 Jianchuan Rd Shanghai 200240 Peoples R China

Oilfields in high or ultra-high water-cut period are of high nonlinearity and heterogeneity, thus complicated in its internal physics mechanism. Corresponding production data is often of small amount due to large timesteps. In addition, numerous mechanism factors that are usually a prerequisite for traditional data-driven prediction methods are to be determined with extra human effort on a well basis, deviating from the intention of oilfield digital transformation. In response to these obstacles, this research proposes an EMD (Empirical Mode Decomposition)-based variable-weight combination model algorithm (EMD-Combined model): It does not require inputs other than its own historical oil production time series, but rather automatically constructs and filters input features via EMD, time-lag reconstruction and Spearman correlation analysis instead. A dynamic Variable-Weight combination Methods of four machine learning models with different strengths is constructed to carry out prediction. Experimental results show that the EMD-Combined model is more accurate than the solely use of any of the four single models listed above, or models solely exerted with EMD without model-wise combination. In terms of the ease of usage, deployment and "stability"of prediction quality, EMD-Combined model offers a possibility of improvement in real-life practice. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Petroleum engineering Petroleum production forecast Machine learning combination algorithm Empirical mode decomposition

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Adaptive combination of affine projection and NLMS algorithms

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SIGNAL PROCESSING 2014年第0期100卷 64-70页

作者： Choi, Jong Hyun Kim, Seung Hun Kim, Sang Woo Pohang Univ Sci & Technol Dept Elect Engn Pohang South Korea Pohang Univ Sci & Technol Dept Creat IT Excellence Engn Pohang South Korea Pohang Univ Sci & Technol Future IT Innovat Lab Pohang South Korea

We propose a novel scheme for combining two adaptation terms of affine projection algorithms with different projection orders and step-sizes. The selection of the mixing parameter that determines the performance of the proposed combination scheme is derived by the largest decrease of the mean-square deviation. The experimental results show that the proposed algorithm exhibits a fast convergence speed and a small steady-state misalignment. Moreover, the proposed algorithm achieves a low computational complexity in the steady-state. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Adaptive filters Affine projection algorithm combination algorithm Adaptation term

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Accuracy of the Enhanced Liver Fibrosis test, and combination of the Enhanced Liver Fibrosis and non-invasive tests for the diagnosis of advanced liver fibrosis in patients with non-alcoholic fatty liver disease

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HEPATOLOGY RESEARCH 2020年第6期50卷 682-692页

作者： Inadomi, Chika Takahashi, Hirokazu Ogawa, Yuji Oeda, Satoshi Imajo, Kento Kubotsu, Yoshihito Tanaka, Kenichi Kessoku, Takaomi Okada, Michiaki Isoda, Hiroshi Akiyama, Takumi Fukushima, Hideaki Yoneda, Masato Anzai, Keizo Aishima, Shinichi Nakajima, Atsushi Eguchi, Yuichiro Saga Univ Fac Med Div Metab & Endocrinol 5-1-1 Nabeshima Saga 8498501 Japan Saga Univ Fac Med Dept Pathol & Microbiol Saga Japan Saga Univ Hosp Liver Ctr Saga Japan Saga Univ Hosp Dept Clin Lab Med Saga Japan Yokohama City Univ Dept Gastroenterol & Hepatol Grad Sch Med Yokohama Kanagawa Japan Siemens Healthcare Diagnost KK Diagnost Business Area Tokyo Japan

Aim The Enhanced Liver Fibrosis (ELF) test comprises a logarithmic algorithm combining three serum markers of hepatic extracellular matrix metabolism. We aimed to evaluate the performance of ELF for the diagnosis of liver fibrosis and to compare it with that of liver stiffness measurement (LSM) by FibroScan in non-alcoholic fatty liver disease. Methods ELF cut-off values for the diagnosis of advanced fibrosis were obtained using receiver operating characteristic analysis in patients with biopsy-confirmed non-alcoholic fatty liver disease (training set;n = 200). Diagnostic performance was analyzed in the training set and in a validation set (n = 166), and compared with that of LSM in the FibroScan cohort (n = 224). Results The area under receiver operating characteristic curve was 0.81 for the diagnosis of advanced fibrosis, and the ELF cut-off values were 9.34 with 90.4% sensitivity and 10.83 with 90.6% specificity in the training set, and 89.8% sensitivity and 85.5% specificity in the validation set. There was no significant difference in the area under the receiver operating characteristic curve between ELF and LSM (0.812 and 0.839). A combination of ELF (cut-off 10.83) and LSM (cut-off 11.45) increased the specificity to 97.9% and the positive predictive value, versus ELF alone. Sequential use of the Fibrosis-4 index (cut-off 2.67) and ELF (cut-off 9.34) increased the sensitivity to 95.9%. Conclusions ELF can identify advanced liver fibrosis in non-alcoholic fatty liver disease, and its diagnostic accuracy is comparable to that of FibroScan. According to the clinical setting, combinations or sequential procedures using other non-invasive tests complement the diagnostic performance of ELF for the identification of advanced fibrosis.

关键词： combination algorithm non-invasive test sequential algorithm vibration-controlled transient elastography

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