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ieeE control and System Graduate Research colloquium (ICSGRC)

作者： Samuel-Soma M. Ajibade Anwar P.P. Abdul Majeed Muhammed Basheer Jasser Ghassan Saleh ALDharhani Ismail Ahmed Al-Qasem Al-Hadi Ganesh Kumar Department of Computing and Information Systems School of Engineering & Technology Sunway University Petaling Jaja Selangor Malaysia Department of Computer Engineering Istanbul Ticaret Universitesi Istanbul Turkiye Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur Malaysia Faculty of Information Science and Technology UKM University Bangi Selangor Malaysia

ISBN: (数字)9798350386554

ISBN: (纸本)9798350386561

A Science mapping analysis was performed on Scopus papers spanning from 2003 to 2022 to investigate the utilization of artificial intelligence techniques in malignant tumors research. The analysis unveiled a progressive rise in publications, amounting to a total of 206, with articles accounting for 55.34% and conference papers making up 44.66%. Zuherman Rustam and Universitas Indonesia made substantial contributions. India's exceptional performance might be due to the availability of financial support from prestigious organizations such as Universitas Indonesia, the National Natural Science Foundation of China, and Brazil's Conselho Nacional de Desenvolvimento Científico e Tecnológico. An investigation of social networks, specifically looking at collaborations between authors, revealed robust international cooperation, which improved the availability of resources and infrastructure. The hotspot research revealed the prominent terms to be genetic algorithms, diseases, and feature extraction. The cluster analysis identified three main areas of focus: Precision Health Analytics, Genomic Cancer Profiling, and Integrated AI Diagnosis. In summary, AIMTR research is actively tackling cancer and oncological concerns through the use of computational approaches, making substantial contributions to both societal and scientific progress.

关键词： Productivity Social networking (online) Genomics Organizations Market research Paper making Artificial intelligence Bioinformatics Cancer genetic algorithms

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Testing Vision-Based control systems Using Learnable Evolutionary algorithms 18

Testing Vision-Based Control Systems Using Learnable Evoluti...

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40th ACM/ieeE International Conference on Software engineering (ICSE)

作者： Ben Abdessalem, Raja Nejati, Shiva Briand, Lionel C. Stifter, Thomas Univ Luxembourg SnT Ctr Luxembourg Luxembourg IEE SA Luxembourg Luxembourg

ISBN: (纸本)9781450356381

Vision-based control systems are key enablers of many autonomous vehicular systems, including self-driving cars. Testing such systems is complicated by complex and multidimensional input spaces. We propose an automated testing algorithm that builds on learnable evolutionary algorithms. These algorithms rely on machine learning or a combination of machine learning and Darwinian genetic operators to guide the generation of new solutions (test scenarios in our context). Our approach combines multiobjective population-based search algorithms and decision tree classification models to achieve the following goals: First, classification models guide the search-based generation of tests faster towards critical test scenarios (i.e., test scenarios leading to failures). Second, search algorithms refine classification models so that the models can accurately characterize critical regions (i.e., the regions of a test input space that are likely to contain most critical test scenarios). Our evaluation performed on an industrial automotive automotive system shows that: (1) Our algorithm outperforms a baseline evolutionary search algorithm and generates 78% more distinct, critical test scenarios compared to the baseline algorithm. (2) Our algorithm accurately characterizes critical regions of the system under test, thus identifying the conditions that are likely to lead to system failures.

关键词： Search-based Software engineering Evolutionary algorithms Software Testing Automotive Software systems

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Parameter extraction of photovoltaic cell using differential evolution method

Parameter extraction of photovoltaic cell using differential...

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ieeE Applied Power Electronics colloquium (IAPEC)

作者： Kashif Ishaque Zainal Salam Hamed Taheri Amir Shamsudin Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia

This paper proposes a new parameter extraction method of photovoltaic cell, based on the differential evolution (DE) technique. The proposed method requires very few control parameters and converges rapidly to a solution. Furthermore, it can fit the I-V curve very accurately irrespective of the values of the initial parameters guesses. The performance of DE is evaluated against the well known genetic algorithm (GA) using a synthetic and experimental I-V data set. It is found that the DE method fits the I-V curve better than GA, has a lower fitness function value and faster execution time.

关键词： genetic algorithms Parameter extraction Convergence Photovoltaic cells Accuracy Photovoltaic systems Data mining

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Topological Design of Industrial Ethernet Networks with a Fast Heuristic

Topological Design of Industrial Ethernet Networks with a Fa...

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15th ieeE International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Zhang, Lei Lampe, Mattias Wang, Zhi Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9781424468508

The recent rapid development of industrial Ethernet requires addressing the topic of network design from a new perspective. The design of industrial Ethernet networks must typically consider real-time constraints and robustness against network failures. In this paper, the topology design of industrial Ethernet networks problem is firstly modelled considering the requirements of industrial applications. Considering the increasing scale of industrial Ethernet networks, computational complexity of network optimization schemes becomes a more and more important issue. A fast algorithm based on a heuristic extension of a genetic algorithm is presented and shown to provide an effective solution and lower computation complexity as compared to a pure genetic algorithm.

关键词： control engineering computing genetic algorithm genetic algorithms industrial Ethernet networks local area networks network topology network topology optimisation real-time constraint real-time systems

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A NOVEL METHOD FOR INPUT SELECTION FOR THE MODELING OF NONLINEAR DYNAMIC systems

A NOVEL METHOD FOR INPUT SELECTION FOR THE MODELING OF NONLI...

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1st Annual Dynamic systems and control Conference (DSCC 2008)

作者： Jiang, Li Latronico, Elizabeth Ni, Jun Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9780791843352

In order to handle increasingly complex engineering applications with highly nonlinear behaviors, various advanced system identification algorithms have been developed for control and diagnostic purposes. Since the performance of these algorithms depends significantly on the selection of input variables, a systematic input selection methodology is needed to identify the nonlinear relation between the input variables and system outputs, even in the presence of high correlation among the candidate input variables. The methodology proposed in this paper converts the problem of selecting appropriate input variables for the identification of a nonlinear dynamic system into one of a set of properly linearized models. In order to enable the approximation of the nonlinear system behavior with a set of linear models, a growing self-organizing map is employed to appropriately partition the system operating region into sub-regions via unsupervised learning. Evaluated based on the minimum description length principle, a model with its most related input variables is then selected using a genetic algorithm so that the computational burden can be reduced. The effectiveness of this methodology has been demonstrated with two simulation examples and a real-world example of modeling the air mass flow rate and intake manifold pressure in a diesel engine airflows system.

关键词： Diesel engines

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Parallel quantum evolutionary algorithm based on chaotic searching technique for multi-modal function optimization

Parallel quantum evolutionary algorithm based on chaotic sea...

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ISECS International colloquium on Computing, Communication, control, and Management, CCCM

作者： Xiao-ming You Xing-wai Miao Sheng Liu College of Electronic and Electrical Engineering Shanghai University Engineering of Science Shanghai China

A novel parallel quantum evolutionary algorithm based on chaotic searching technique (PCQEA) is proposed. In the algorithm, the use of a chaotic searching technique provides this methodology with superior global search ability; several antibody diversification schemes were incorporated into the algorithm in order to enhance the exploitation and exploration. It can help to obtain the multi-modal optimal solutions rapidly. The technique for improving the performance of PCQEA has been described; simulation experiments result shows that the proposed method surpasses the traditional models in regard to the convergence speed.

关键词： Evolutionary computation Chaos Quantum computing Chaotic communication Concurrent computing Quantum mechanics Parallel processing genetic algorithms Learning systems Performance analysis

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An incremental adaptive life long learning approach for type-2 fuzzy embedded agents in ambient intelligent environments

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ieeE TRANSACTIONS ON FUZZY systems 2007年第1期15卷 41-55页

作者： Hagras, Hani Doctor, Faiyaz Callaghan, Victor Lopez, Antonio Univ Essex Dept Comp Sci Colchester CO4 3SQ Essex England Univ Oviedo Dept Elect Engn Gijon 33204 Asturias Spain

In this paper, we present a novel type-2 fuzzy systems based adaptive architecture for agents embedded in ambient intelligent environments (AIEs). Type-2 fuzzy systems are able to handle the different sources of uncertainty and imprecision encountered in AlEs to give a very good response. The presented agent architecture uses a one pass method to learn in a nonintrusive manner the user's particular behaviors and preferences for controlling the AIE. The agent learns the user's behavior by learning his particular rules and interval,type-2 Membership Functions (MFs), these rules and MFs can then be adapted online incrementally in a lifelong learning mode to suit the changing environmental conditions and user preferences. We will show that the type-2 agents generated by our one pass learning technique outperforms those generated by genetic algorithms (GAs). We will present unique experiments carried out by different users over the course of the year in the Essex Intelligent Dormitory (iDorm), which is a real AIE test bed. We will show how the type-2 agents learnt and adapted to the occupant's behavior whilst handling the encountered short term and long term uncertainties to give a very good performance that outperformed the type-1 agents while using smaller rule bases.

关键词： ambient intelligent environment embedded agents interval type-2 fuzzy systems learning

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engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology

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iee PROCEEDINGS-NANOBIOTECHNOLOGY 2006年第4期153卷 81-101页

作者： Wikswo, J. P. Prokop, A. Baudenbacher, F. Cliffel, D. Csukas, B. Velkovsky, M. Vanderbilt Univ Inst Integrat Biosyst Res & Educ Nashville TN 37235 USA Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA Vanderbilt Univ Dept Mol Physiol & Biophys Nashville TN 37235 USA Vanderbilt Univ Dept Phys & Astron Nashville TN 37235 USA Vanderbilt Univ Dept Chem Engn Nashville TN 37235 USA Vanderbilt Univ Dept Chem Nashville TN 37235 USA Kaposvar Univ Inst Math & Informat Technol H-7400 Kaposvar Hungary

systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 106 dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 106 model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth;secondly, the ability to open existing internal control and signalling loops;thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators;and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

关键词： cellular control loops Bioelectric signals Physics of subcellular structures microfluidics nanoinstruments genetic information electrical environment mechanical environment metabolic variables BioNEMS Bioelectricity microdevices genetics cellular biophysics biocontrol dynamic cellular signalling intracellular nanoactuators genes quantitative physiology dynamic physiology postgenomic physiology MEMS and NEMS device technology microinstruments microactuators BioMEMS microactuators microarray expression profiles proteins microelectrode systems biology Physical chemistry of biomolecular solutions and condensed states nanodevices proteomic information cellular measurements external control molecular biophysics biochemical environment fluorescence postproteomic physiology Micromechanical and nanomechanical devices and systems computational vision multiscale physiology critical intracellular biochemical events Nanotechnology applications in biomedicine bioelectric phenomena Microactuators biochemistry nanotechnology

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Simulation and experimental studies of hybrid learning control with acceleration feedback for flexible manipulators

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8th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2005

作者： Md Zain, M.Z. Alam, M.S. Tokhi, M.O. Mohamed, Z. Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Malaysia

ISBN: (纸本)3540264132

This paper presents investigations at developing a hybrid iterative learning control scheme with acceleration feedback (PDILCAF) for flexible robot manipulators. An experimental flexible manipulator rig and corresponding simulation environment are used to demonstrate the effectiveness of the proposed control strategy. In this work the dynamic model of the flexible manipulator is derived using the finite element (FE) method. A collocated proportional- derivative (PD) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate iterative learning control with acceleration feedback and genetic algorithms (GAs) for optimization of the learning parameters for control of vibration (flexible motion) of the system. The system performance with the controllers is presented and analysed in the time and frequency domains. The performance of the hybrid learning control scheme without and with acceleration feedback is assessed in terms of input tracking, level of vibration reduction at resonance modes and robustness with various. © 2006 Springer-Verlag Berlin Heidelberg.

关键词： genetic algorithms

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Application of combined feasible-direction method and genetic algorithm to optimal planning of harmonic filters considering uncertainty conditions

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iee PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION 2005年第5期152卷 729-736页

作者： Chang, YP Tseng, WK Tsao, TF Department of Electrical Engineering Nan Kai Institute of Technology Taiwan ROC

The paper presents an approach of combining a feasible-direction method and a genetic algorithm (FDM + GA) to investigate the planning of large-scale passive harmonic filters. The optimal filter scheme can be obtained for a system under abundant harmonic-current sources where harmonic-amplification problems should be avoided. The design is to minimise the total demand distortion of harmonic currents and total harmonic distortion of load bus voltages. Filter loss, reactive-power compensation and constraints of individual harmonics can be considered in the design procedures. The constraints of harmonics with orders lower than the filter tuned points have been set stricter to avoid amplification of noncharacteristic harmonics. The search for the global optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC are furnaces are used and a static Var compensator (SVC) is installed. Three design schemes are compared to demonstrate the performance of the proposed method. Finally, expectations and standard deviations of objective functions are used to present effects of filter-parameter detuning, loading uncertainty and changes of system impedance.

关键词： steel plant load bus voltage distortion harmonic filter Passive filters and other passive networks harmonic constraint DC arc furnaces loading uncertainty harmonic current distortion Power and energy control Optimisation techniques standard deviation electric current control arc furnaces genetic algorithms objective function genetic algorithm Other power apparatus and electric machines power harmonic filters reactive power control optimal planning filter tuned point electric impedance filter-parameter detuning static VAr compensator Power supply quality and harmonics Power applications in metallurgical industries Process heating harmonic distortion power supply quality steel industry feasible-direction method control of electric power systems passive filters Current control Voltage control reactive-power compensation static VAr compensators harmonic-amplification problem voltage control harmonic-current sources AC arc furnaces SVC filter loss system impedance global optimal solution

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