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International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Yajuan Zhang Xiuyan Zheng Sihan Yang Shangyu Meng Z. Y. Yang Xinghui Fei College of Information Engineering Hainan Vocational University of Science and Technology Haikou Hainan China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Network engineer department Guiyang Shengteng Network Technology Co. LTD Guiyang China Electrical and Computer Engineer Deparment Colorado State University Fort Collins U.S.

ISBN: (数字)9798350385106

ISBN: (纸本)9798350385113

Random forest models often rely on human-determined parameters, which may introduce subjectivity and affect the degree of optimization of the model. To address this issue, we use a random forest approach based on Bayesian optimization to reduce the influence of human factors and improve the fitting. Bayesian optimization prevents the model from falling into the dilemma of local optimum. In order to show the effect of the optimization, we compare the support vector machine, the original random forest and the LGBM model, and perform Bayesian optimization on the latter two to achieve better results. Experiments show that the optimized model performs well in stock return prediction with a reduction of 0.01 in RMSE and MAE, a reduction of 0.4 in MAPE, and an improvement of 0.02 in R2 value compared to the other models. The Bayesian optimization based Random Forest model achieves the lowest prediction error on different datasets and has wide applicability.

关键词： Support vector machines Accuracy Time series analysis Human factors Predictive models Data models Bayes methods

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Evaluating Length of a Shortest Adaptive Homing Sequence for Weakly Initialized FSMs

Evaluating Length of a Shortest Adaptive Homing Sequence for...

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2020 IEEE East-West Design and Test Symposium, EWDTS 2020

作者： Vinarskii, Evgenii Yevtushenko, Nina Lomonosov Moscow State University Department of Computer Science Moscow Russia Ivannikov Institute for System Programming of Ras Software Engineering Deparment Moscow Russia

ISBN: (数字)9781728198996

ISBN: (纸本)9781728198996

There are many research papers devoted to the state identification problem of finite state machines (FSMs) which are widely used for analysis of discrete event systems. A deterministic complete reduced FSM always has a homing sequence (HS) but a number of non-deterministic FSMs not necessarily have a preset HS;nevertheless, those FSMs can still have an adaptive HS. Moreover, adaptive HS can be shorter than the preset. If each state can be an initial state of a complete FSM, i.e., an FSM is non-initialized, then a shortest adaptive HS (if it exists) has polynomial length in the number of FSM states. We show that it is not the case for weakly-initialized FSMs: such FSMs can have a shortest adaptive HS of exponential length in the number of FSM states/transitions. However, the experimental evaluation shows that the non-polynomial upper bound for a shortest adaptive HS was never reached for randomly generated weakly-initialized two-input FSMs. © 2020 IEEE.

关键词： Adaptive homing sequence Non-deterministic FSM weakly initialized FSM

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Online identification of nonlinear systems using neo-fuzzy supported brain emotional learning network

Online identification of nonlinear systems using neo-fuzzy s...

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作者： Farooq, Umar Gu, Jason Asad, Muhammad Usman Abbas, Ghulam Hanif, Athar Balas, Marius Department of Electrical Computer Engineering Dalhousie University Halifax Canada Department of Automatics and Applied Software University 'Aurel Vlaicu' Arad Romania Deparment of Electrical Engineering University of Lahore Pakistan Center for Automotive Research Ohio State University ColumbusOH United States Department of Electrical Engineering University of the Punjab Pakistan

This paper proposes an online algorithm for identifying the nonlinear dynamical systems and is termed as neo-fuzzy based brain emotional learning plant identifier (NFBELPI). As the name suggests, the proposed identifier is a combination of brain emotional learning network and neo-fuzzy neurons. The integration of these two networks is realized in a way that retains the characteristics of both the networks while an enhanced performance is achieved at the same time. Precisely, the orbitofrontal cortex section of the brain emotional learning network is fused with neo-fuzzy neurons with a view to equip it with more knowledge than does the amygdala section possesses. The proposed identifier accepts n-input and m-output samples to generate an estimate of the plant output and employs a brain emotional learning algorithm to lower the estimation error by adjusting a total of ((n + m + 1) × p) + (n + m + 2) weights, with p being the number of neo-fuzzy neurons. The proposal is validated in a MATLAB programming environment using a simulated Narendra dynamical plant as well as against the data recorded from real forced duffing oscillator. Comparison with a brain emotional learning plant identifier (BELPI) and some other state-of-the art identifiers in terms of root mean squared error (RMSE) criterion reveals the improved performance of the proposed identifier. © 2020 - IOS Press and the authors. All rights reserved.

关键词： MATLAB

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A Strategy Transfer and Decision Support Approach for Epidemic Control in Experience Shortage Scenarios

arXiv

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arXiv 2024年

作者： Xiao, Xingyu Chen, Peng Cao, Xue Liu, Kai Deng, Li Zhao, Dongjia Chen, Zhe Deng, Qing Yu, Feng Zhang, Hui Research Institute of Macro-Safety Science University of Science and Technology Beijing Beijing100083 China School of Civil and Resource Engineering University of Science and Technology Beijing Beijing100083 China Institute of Nuclear and New Energy Technology Tsinghua University Beijing100084 China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Institute of Software Chinese Academy of Sciences Beijing100049 China Central South Architectural Design Institute Co. Wuhan430071 China Xi’an Jiao Tong University Xi’an713599 China Shanxi University Taiyuan030006 China Shanghai Jiao Tong University Shanghai200030 China Deparment of Engineering Physics Tsinghua University Beijing100091 China

Epidemic outbreaks can cause critical health concerns and severe global economic crises. For countries or regions with new infectious disease outbreaks, it is essential to generate preventive strategies by learning lessons from others with similar risk profiles. A Strategy Transfer and Decision Support Approach (STDSA) is proposed based on the profile similarity evaluation. There are four steps in this method: (1) The similarity evaluation indicators are determined from three dimensions, i.e., the Basis of National Epidemic Prevention & Control, Social Resilience, and Infection Situation. (2) The data related to the indicators are collected and preprocessed. (3) The first round of screening on the preprocessed dataset is conducted through an improved collaborative filtering algorithm to calculate the preliminary similarity result from the perspective of the infection situation. (4) Finally, the K-Means model is used for the second round of screening to obtain the final similarity values. The approach will be applied to decision-making support in the context of COVID-19. Our results demonstrate that the recommendations generated by the STDSA model are more accurate and aligned better with the actual situation than those produced by pure K-means models. This study will provide new insights into preventing and controlling epidemics in regions that lack experience. © 2024, CC BY-NC-ND.

关键词： Decision support systems

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Thematical and Impact Differences Between National and International Collaboration on Artificial Intelligence Research

Thematical and Impact Differences Between National and Inter...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： A. Velez-Estevez P. Garcia-Sanchez J.A. Moral-Munoz M.J. Cobo Deparment of Computer Science and Engineering University of Cádiz Spain Department of Software Engineering University of Granada Spain Department of Nursing and Physiotherapy University of Cádiz Spain

ISBN: (数字)9781728143842

ISBN: (纸本)9781728143859

In this paper, an analysis to discover the impact differences in terms of citations between three levels of research collaboration is carried out. Thus, the objective, further than discover what kind of collaboration is more rewarding in terms of impact, is to determine if researchers cover different themes when they collaborate with people from other countries or universities within the same country, and if those themes get more citations. To this end, 12610 documents belonging to the "computer Science & Artificial Intelligence" Web of Science subject category, and published in 2015 were analyzed. The whole corpus was divided into three different datasets, according to the defined collaboration levels (local, national and international). Results indicate that papers by authors from different countries receive more citations in average, but also, there exist some differences with respect to the research themes between the datasets.

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Developing SPIM-TA: a maturity-level framework for systematic process improvement in software testing automation

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Ain Shams engineering Journal 2025年第8期16卷

作者： Muhammad Faisal Abrar Yasser Alharbi Muhammad Alsaffar Shah Hussain Muhammad Saqib Jawad Khan Youngmoon Lee College of Computer Science & Engineering University of Ha’il Ha’il 2440 Saudi Arabia Department of Information and Computer Science University of Ha’il Ha'il 2440 Saudi Arabia Department of Mathematics College of Science University of Ha’il Ha’il 2440 Saudi Arabia Department of Software Engineering University of Engineering & Technology Peshawar 25000 Pakistan School of Computing Gachon University Seongnam 13120 Republic of Korea Deparment of Robotics Hanyang University Ansan 15588 Republic of Korea

The growing complexity and demands for high-quality software underlined the need for robust automated software testing frameworks. However, lack of skilled personnel, cost of testing automation, and maintenance of script along with others oppose the widespread adoption of automation in testing. The work proposed by this study is in line with the development of Systematic Process Improvement Model for Testing Automation, abbreviated as SPIM-TA. The model is inspired from Capability Maturity Model Integration (CMMI) and software Outsourcing Vendor Readiness Model (SOVRM) maturity-level-based framework. The research was done based on a four-phased methodology. In the first phase, a systematic literature review identified 14 critical challenges in software testing automation with practices or solutions for each of these challenges. In the second round, a survey questionnaire is used to validate these findings in industrial context and extract more practical insights from case studies. This dual approach had ensured both academic rigor and the relevance of the practices with industry. The third one involved developing SPIM-TA by incorporating insights that come from the SLR and those results of the survey as well. The framework defines five maturity levels, systematically addressing the identified challenges and providing a structured pathway for organizations to enhance their automation processes. In the fourth phase, case studies of industrial applications were carried out to evaluate SPIM-TA’s efficiency. The applicability, scalability, and impact of the framework on testing automation in the real world were assessed using the Motorola Assessment Tool. The findings illustrate the systematic way SPIM-TA will help overcome the automation challenge, so that organizations can reach more advanced levels of maturity and efficiency in their testing processes. In the first place, the present study closes the gap between academia and industry but at the same time paves the fou

关键词： Automated software Testing SPIM-TA framework Systematic Process Improvement

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Deriving adaptive homing sequences for weakly initialized nondeterministic FSMs

Deriving adaptive homing sequences for weakly initialized no...

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2019 IEEE East-West Design and Test Symposium, EWDTS 2019

作者： Vinarskii, Evgenii Tvardovskii, Aleksandr Evtushenko, Larisa Yevtushenko, Nina Computer Science Department Lomonosov Moscow State University Moscow Russia Radiophysical Department Tomsk State University Tomsk Russia Software Engineering Deparment Ivannikov Institute for System Programming Moscow Russia

ISBN: (纸本)9781728110035

State identification sequences, such as homing and distinguishing sequences (HS and DS), are widely used in FSM (Finite State Machine) based testing in order to reduce the size of a returned complete test suite as well as minimize checking efforts in passive testing. Preset HS are known to always exist for deterministic complete reduced FSMs but it is not the case for nondeterministic FSMs. It is also known that in this case, adaptive HS exist more often and usually are shorter than the preset. Nowadays, a number of specifications are represented by nondeterministic FSMs and thus, a deeper study of such sequences is required. There exist sufficient and necessary conditions for the existence of an adaptive HS for complete nondeterministic FSMs when each state can be an initial state but those conditions become only sufficient for weakly initialized FSMs where only some states are initial. In this paper, we propose sufficient and necessary conditions for a weakly initialized FSM to have an adaptive homing sequence, possibly up to given length, which are based on deriving an appropriate so-called homing FSM. The experimental evaluation of the existence of adaptive and preset HS is performed for randomly generated FSMs. © 2019 IEEE.

关键词： Well testing

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Synchronous composition of quasi-complete and quasi-deterministic FSMs

Synchronous composition of quasi-complete and quasi-determin...

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International Conference on Actual Problems of Systems and software engineering

作者： Igor Burdonov Alexandr Kossachev Nina Yevtushenko Tiziano Villa Software Engineering department Ivannikov Institute for System Programming of RAS Software engineering deparment Ivannikov Institute for System Programming Computer Science Department University of Verona

ISBN: (纸本)9781728160627

In this paper, we consider the synchronous composition of Finite State Machines (FSMs) that corresponds to instantaneous communication of hardware components. Such FSMs can be deterministic or nondeterministic, partial or complete. We first extend the existing synchronous composition operator from a pair of components to a collection of components with multiple input and output ports, and provide a procedure to compute the composition working directly on the collection of transition tables of the component FSMs. Then, based on the notion of input-output Moore pair (the output is not sensitive to the input), we prove the following sufficient condition: if the composition has the property that every cycle of ports has a component with a Moore pair, then the class of quasi-complete and quasi-deterministic FSMs is closed under the proposed synchronous composition.

关键词： Finite state machine (FSM) Quasi-deterministic FSM Quasi-complete FSM Moore pair Synchronous composition Pairing multi-input output ports harbors finite state machines deterministic

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Ontology-Based software Requirements Reuse: Case Study in Fire Control software Product Line Domain

Ontology-Based Software Requirements Reuse: Case Study in Fi...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Elif Kamer Karatas Baris Iyidir Aysenur Birtürk Software Engineering Department Defense Systems Technologies Division Aselsan Inc. Ankara Turkey Computer Engineering Deparment Middle East Technical University Ankara Turkey

ISBN: (纸本)9781479942732

Reuse is a highly favored concept in software engineering community, but it is the essence of successful software Product Line (SPL) development, which enables the reuse of different types of software artifacts. Focus of this paper is on the reuse of SPL requirements: an ontology-based requirements reuse method is introduced for systematic reuse of product line requirements which is composed of an ontology-based approach for reusable requirements definition and a requirements configuration approach for the reuse of requirements. Evaluation of the introduced approach is performed on fire control software projects and results are discussed.

关键词： software Ontologies Systematics Unified modeling language Semantics Knowledge based systems Object oriented modeling

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Geolocation on the iPhone by automatic street sign reading

Geolocation on the iPhone by automatic street sign reading

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25th International Conference of Image and Vision Computing New Zealand, IVCNZ 2010

作者： Oosterman, Joshua Green, Richard Deparment of Computer Science and Software Engineering University of Canterbury Chrischurch New Zealand

ISBN: (纸本)9781424496303

In any country, roads are marked with signs. In particular, street signs are a type of road sign used to display the names of streets. Mobile devices such as smart phones are now powerful enough to serve as platforms for computer vision applications. These mobile devices are commonly equipped with high resolution cameras and increasingly with internal GPS for *** propose an accurate method of geolocation which detects, segments and reads street signs in complex natural scenes from an iPhone image. Street signs are detected using image segmentation based on edge detection and contour detection techniques. Sign candidates are selected using several heuristics, and then partitioned into individual characters. The letters are recognised using a nearest-neighbour algorithm for Optical Character Recognition (OCR). The street names finally are passed to a GeoCoding API to display a street map of the users location. We evaluate the system for a real word data set and achive 75% sign detection accuracy, 91% OCR accuracy and 55% total geolocation accuracy. © 2010 IEEE.

关键词： Optical character recognition

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