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19th International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Radu, Petru Regep, Cezar Valeriu Continental Automot Romania Adv Driver Assistance Syst Timisoara Romania

ISBN: (纸本)9781538626269

In recent years, Advanced Driver Assistance Systems (ADAS) for automotive industry has been increasingly using camera-based algorithms to detect various events that occur whilst driving. Usually, several computer vision algorithms run concurrently by processing frames grabbed from the windscreen camera. For a normal operation of camera-based ADAS algorithms, is mandatory that the field of view of the camera is not obstructed by noise factors. In this paper, an algorithmic fusion approach is explored to observe how two different methods for obstruction detection of camera's field of view improve the detection rate when fused. The first obstruction detection algorithm relies on classical image processing operations, while the second obstruction detection algorithm employs a machine learning approach during its functioning. The present work investigates how the stability of the windscreen blockage detection is enhanced by employing trainable and non-trainable fusion techniques. The results are validated on numerous recordings from a range of vehicles and driving conditions.

关键词： camera blockage autonomous vehicle self-driving car algorithm fusion

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Detection filters and algorithm fusion for ATR

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1997年第1期6卷 114-125页

作者： Casasent, D Ye, AQ TELXON METANET FT MYERSFL 33907

Detection involves locating all candidate regions of interest (objects) in a scene independent of the object class with object distortions and contrast differences, etc., present, It is one of the most formidable problems in automatic target recognition, since it involves analysis of every local scene region, We consider new detection algorithms and the fusion of their outputs to reduce the probability of false alarm P-FA while maintaining high probability of detection P-D. Emphasis is given to detecting obscured targets in infrared imagery.

关键词： .Fig shows alarms Gabor wavelet algorithm fusion aspect views

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Research on the optimization strategy of lithium battery electrode correction system based on algorithm fusion

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第2期44卷 2503-2523页

作者： Xiao, Yanjun Zhao, Churui Qi, Hao Liu, Weiling Meng, Zhaozong Peng, Kai Hebei Univ Technol Sch Mech Engn Tianjin Key Lab Power Transmiss & Safety Technol Tianjin Peoples R China Career Leader Intelligent Control Automat Co Suqian Jiangsu Peoples R China

In the control system of a lithium battery rolling mill, the correction system was crucial. This was because the correction system had a significant impact on the performance of the lithium battery rolling mill, including high precision and efficient rolling quality. However, the non-linearity of the correction system and the uncertainty of the correction system made it a challenging problem to achieve a high precision correction control. The contribution and innovation of this paper was a genetic fuzzy PID control strategy based on Kalman filter, which was proposed and applied to the control of lithium battery rolling mill correction technology. In order to achieve intelligent control of a high-precision electrode rolling mill correction system, an algorithm fusion control scheme was proposed. Firstly, a novel and detailed correction system model was presented. Next, the initial PID parameters of the correction were optimized by means of a genetic algorithm so that the PID parameters could be adapted to the correction control process and then optimized again by adding an extended Kalman filter. Finally, the lithium battery rolling mill correction control system was validated, tested and commissioned in the field. The results showed that the designed algorithm could meet the working requirements of the lithium battery rolling mill and that it improved the accuracy of the correction system. In the actual lithium battery rolling mill production process, the algorithm was compared with a conventional PID. Compared with the common single algorithm, the fusion algorithm proposed in this paper was a complete set of high precision correction control system algorithm to solve the high precision problem faced by the correction system in the actual lithium battery rolling mill correction system.

关键词： Pole piece rolling mill deviation correction system fuzzy PID genetic algorithm algorithm fusion extended kalman filter

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CNC machine tool thermal error robust state space model based on algorithm fusion

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2021年第3-4期116卷 941-958页

作者： Liu, Yunsheng Miao, Enming Liu, Hui Feng, Ding Zhang, Mingde Li, Jiangang Chongqing Univ Technol Sch Mech Engn Chongqing 400054 Peoples R China Hefei Univ Technol Sch Instrument Sci & Optoelect Engn Hefei 230009 Peoples R China Xian Univ Posts & Telecommun Sch Automat Xian 710121 Peoples R China Yangtze Univ Sch Mech Engn Jingzhou 434023 Peoples R China Harbin Inst Technol Shenzhen Shenzhen 518055 Peoples R China

Thermal error is one of the main sources of errors in CNC machine tools. The thermal error characteristics of CNC machine tools will change with changes in machine temperature and machine operating parameters. An excellent thermal error model should have good prediction accuracy and prediction robustness on the premise of high-precision fitting of thermal error. Based on the Leaderway-V450 CNC machine tool, 18 batches of thermal error measurement experiments are conducted in different periods and rotating speeds throughout the year. Moreover, the change in the thermal error law caused by the coupling of temperature change and spindle rotating speed change is studied. After an in-depth analysis of the ridge regression and state space algorithms, a robust state space model (RSSM) is proposed by combining the advantages of the ridge regression algorithm in eliminating collinearity between independent variables on model robustness and that of the state space algorithm in describing system internal structure and characteristics. RSSM is compared with the multiple linear regression model (MLRM), ridge regression model (RRM) and state space model (SSM). RSSM based on the algorithm fusion is proven to realise the comprehensive description of the relationship between the thermal error of machine tool, temperature increase of temperature sensitive point and spindle speed. Moreover, RSSM has superior model accuracy and prediction robustness under the influence of change in temperature and spindle speed. The mathematical model is ultimately used to accurately describe engineering phenomena and laws. In engineering application, different algorithm features should be extracted according to the laws of engineering objects to integrate them, thereby meeting the actual engineering laws, so that the established model can have sufficient prediction accuracy and also meet the engineering needs of robustness. This research systematically studied the realisation of the RRM and SSM algori

关键词： Thermal error CNC machine tools algorithm fusion Robustness State space model Ridge regression model

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Effect of algorithm fusion and aggregation methodologies on the performance of a corrosion detection algorithm

Effect of algorithm fusion and aggregation methodologies on ...

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Conference on Multisensor, Multisource Information fusion

作者： Nelson, BN Slebodnick, P Groeninger, W Lemieux, EJ GEO CENTERS INC Newton Ctr MA 02459 USA

ISBN: (纸本)0819457981

Over the last several years, the Naval Research Laboratory has been developing corrosion detection algorithms for assessing coatings conditions in tank and voids on US Navy Ships. The corrosion detection algorithm is based on four independent algorithms;two edge detection algorithms, a color algorithm and a grayscale algorithm. Of these four algorithms, the color algorithm is the key algorithm and to some extent drives overall algorithm performance. The four independent algorithm results are fused with other features to first generate an image level assessment of coatings damage. The image level results are next aggregated across a tank or void image set to generate a single coatings damage value for the tank or void being inspected. The color algorithm, algorithm fusion methodology and aggregation algorithm components are key to the overall performance of the corrosion detection algorithm. This paper will describe modifications that have been made in these three algorithm components to increase the corrosion detection algorithmis overall operating range, to improve the algorithmis ability to assess low coatings damage and to improve the accuracy of coatings damage classification at both the individual image as well as at the whole tank level.

关键词： information fusion image processing algorithm fusion corrosion detection algorithms

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An algorithm fusion for land-based warning system to enhance detection and tracking performance

An algorithm fusion for land-based warning system to enhance...

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14th Conference on Signal and Data Processing of Small Targets

作者： Park, YW Lee, BW Park, JS Kim, DJ Agcy Def Dev Taejon 305600 South Korea

ISBN: (纸本)0819444782

An algorithm fusion approach is presented to detect a short range target in the land enviromnents with heavy clutters. There has been fundamental problems in extracting the small target from cluttered IR images in a land-based IR Sensor. One of the causes is that we do not have sufficient time to make a decision. In addition, high false alarm and low detection rate make it more difficult to track consecutively without disconnection. It is also found that the target occupies 5 to 7 pixels or more ones in sometimes when it approaches to the counter decision range. When the target is maneuvering the classical matched filter with Gaussian-shaped target assumption generates more false alarm and make it more difficult to track precisely. In order to overcome some of the difficulties, we combined two algorithms. One is the morphological nonlinear filter which is sensitive to the size of the target. The other is the classical matched filter applied to some of the clustered objects. One of the advantages of using morphological filter is that it requires less calculation time than the classical matched filter. It also provides mote effective clues when the target is passing the decision range with predetermined target size. In order to reduce the false detection, two dimensional structuring elements are separated to one dimensional elements and applied opening minus closing operation to remove the longitudinal and lateral line objects abundant in the land background. In addition, real time calculation of matched filter based on the object clustering is proposed to implement in real system.

关键词： matched filters mophological filter target detection algorithm fusion infra-red

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On the power of algorithm fusion

On the power of algorithm fusion

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Conference on Detection and Remediation Technologies for Mines and Minelike Targets VI

作者： Dobeck, GJ NSWC Coastal Syst Stn Div Dahlgren Panama City FL 32407 USA

The fusion of multiple detection/classification algorithms is proving a very powerful approach for dramatically reducing false alarm rate, while still maintaining a high probability of detection and classification. Th... 详细信息

ISBN: (纸本)0819440892

关键词： mine detection automatic detection automatic classification automatic target recognition algorithm fusion sensor fusion and data fusion

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Robust score-based feature vectors for algorithm fusion

Robust score-based feature vectors for algorithm fusion

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Conference on Detection and Remediation Technologies for Mines and Minelike Targets IX

作者： Dobeck, GJ USN Surface Warfare Ctr Panama City FL 32407 USA

ISBN: (纸本)0819453382

A new technique for constructing score-based feature vectors for algorithm fusion is presented. algorithm fusion is the combining (fusing) of the outputs of multiple detection and classification (D/C) algorithms to generate a final target/nontarget decision. A 2-class D/C problem is considered: Target and Nontarget. It is assumed that multiple D/C algorithms are used to process that same raw sensor data. It is further assumed that each algorithm produces a nonnegative score for each detected object that is a measure of the degree of "target-likeness." (A score of zero is assigned to any D/C algorithm that did not detect a particular object that had been detected by another algorithm.) Several new score-based feature vectors are constructed using only the scores of the individual D/C algorithms. The feature vectors can be used as input to any feature-based classifier;for this paper, the 2-class linear classifier based on maximizing the Fisher ratio criterion has proven very effective. The different score-based feature vectors have different dimensionality. In light of Bellman's curse of dimensionality, this permits one to select the feature vector whose size is most compatible with the size of the training data set. Consequently, robust performance can be achieved.

关键词： sea mines naval mines automatic detection automatic classification sensor fusion data fusion algorithm fusion side-looking sonar side-scan sonar sonar imagery Fisher-ratio

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SAFETY IN THE FACE OF UNKNOWN UNKNOWNS: algorithm fusion IN DATA-DRIVEN ENGINEERING SYSTEMS 44

SAFETY IN THE FACE OF UNKNOWN UNKNOWNS: ALGORITHM FUSION IN ...

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Kshetry, Nina Varshney, Lav R. Ensaras Inc Champaign IL 61821 USA Univ Illinois Urbana IL USA

ISBN: (纸本)9781479981311

Most current machine learning algorithms make highly confident yet incorrect classifications when faced with unexpected test samples from an unknown distribution different from training;such epistemic uncertainty (unknown unknowns) can have catastrophic safety implications. In this conceptual paper, we propose a method to leverage engineering science knowledge to control epistemic uncertainty and maintain decision safety. The basic idea is an algorithm fusion approach that combines data-driven learned models with physical system knowledge, to operate between the extremes of purely data-driven classifiers and purely engineering science rules. This facilitates the safe operation of data-driven engineering systems, such as wastewater treatment plants.

关键词： AI safety algorithm fusion epistemic uncertainty metacognition wastewater treatment

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MSFPSO: Multi-algorithm integrated particle swarm optimization with novel strategies for solving complex engineering design problems

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2025年 437卷

作者： Shu, Bin Hu, Gang Cheng, Mao Zhang, Cunxia Xian Univ Technol Dept Appl Math Xian 710054 Peoples R China Shaanxi Xueqian Normal Univ Dept Math & Stat Xian 710100 Peoples R China

Particle swarm optimization (PSO) is considered among the best seminal meta-heuristic algorithms,boasting merits of minimal parameter requirements, straightforward implementation, and highly accelerated convergence capacity, lower computational complexity, etc. Nevertheless, it also has drawbacks, for instance, it tends to converge prematurely at local optima, lack of diversity, and low accuracy. In order to effectively overcome these shortcomings, this paper presents a multi-strategy fusion enhanced PSO called MSFPSO algorithm. Firstly,It motivated by the black-winged kite algorithm, a migration mechanism based on Cauchy's variation is introduced. This mechanism contributes to the efficiency and effectiveness of the algorithm in exploiting the present search area. Also, it effectively balances the dynamics relationship between exploration and exploitation, boosting the algorithm's global and local search ***, a jointopposition selection strategy is introduced for expanding the solution search range. Our approach is designed to avoid getting stuck in local optima. Specifically, selective opposition obtains the proximity dimension of a candidate solution through a linearly decreasing threshold. Dynamic opposition further extends the process of investigating the solution space. The algorithm is fully incorporated with the differential creative search algorithm for dual-strategy scenarios to enhance the performance of the decision-making effectiveness, population diversity, exploitation capability of the PSO. Finally, an attraction-rejection optimization strategy is introduced to further obtain a good exploitation-exploration balance capability and avoid stagnation of the algorithm. In addition, the comparison results with eight advanced optimization algorithms and six improved particle swarm optimization algorithms on CEC2020 test sets, and the statistical analysis was conducted by Wilcoxon rank sum test. It illustrate the features of the MSFPSO develo

关键词： Particle swarm optimization Cauchy variation Joint adversarial selection Differential creative search Attraction-rejection algorithm fusion

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