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Relevant bibliographies by topics / Single Input Rule Module (SIRM)

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Academic literature on the topic 'Single Input Rule Module (SIRM)'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Single Input Rule Module (SIRM)"

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Yaw, Chong Tak, Shen Young Wong, and Keem Sian Yap. "An ELM-based single input rule module and its application in power generation." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 1 (2020): 359. http://dx.doi.org/10.11591/ijpeds.v11.i1.pp359-366.

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Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. In traditional fuzzy inference method which was the "if-then" rules, all the input and output objects were assigned to antecedent and consequent component respectively. However, a major dilemma was that the fuzzy rules' number kept increasing until the system and arrangement of the rules became complicated. Therefore, the single input rule modules connected type fuzzy inference (SIRM) method where consociated the ou

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Chong, Tak Yaw, Young Wong Shen, and Sian Yap Keem. "An ELM-based single input rule module and its application in power generation." International Journal of Power Electronics and Drive System (IJPEDS) 11, no. 1 (2020): 359–66. https://doi.org/10.11591/ijpeds.v11.i1.pp359-366.

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Abstract:

Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. In traditional fuzzy inference method which was the "if-then" rules, all the input and output objects were assigned to antecedent and consequent component respectively. However, a major dilemma was that the fuzzy rules' number kept increasing until the system and arrangement of the rules became complicated. Therefore, the single input rule modules connected type fuzzy inference (SIRM) method where cons

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3

Yubazaki, Naoyoshi, Jianqiang Yi, and Kaoru Hirota. "SIRMs (Single Input Rule Modules) Connected Fuzzy Inference Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 1, no. 1 (1997): 23–30. http://dx.doi.org/10.20965/jaciii.1997.p0023.

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A new fuzzy inference model, SIRMs (Single Input Rule Modules) Connected Fuzzy Inference Model, is proposed for plural input fuzzy control. For each input item, an importance degree is defined and single input fuzzy rule module is constructed. The importance degrees control the roles of the input items in systems. The model output is obtained by the summation of the products of the importance degree and the fuzzy inference result of each SIRM. The proposed model needs both very few rules and parameters, and the rules can be designed much easier. The new model is first applied to typical second

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Ren, Weina, Chengdong Li, and Peng Wen. "A novel purification machine and fuzzy inference method based hybrid model for wind speed forecasting." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 4059–70. http://dx.doi.org/10.3233/jifs-200205.

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As one kind of readily available renewable energy sources, wind is widely used in power generation where wind speed plays an important role. Generally speaking, we need to forecast the wind speed for improving the controllability of wind power generation. However, there exists considerable randomness and instabilities in wind speed data so that it is difficult to obtain accurate forecasting results. In this paper, we propose a novel fuzzy inference method based hybrid model for accurate wind speed forecasting. In this hybrid model, we adopt two strategies to enhance the estimation performance.

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Yi, Jianqiang, Naoyoshi Yubazaki, and Kaoru Hirota. "Trajectory Tracking Control of Unconstrained Object Using the SIRMs Dynamically Connected Fuzzy Inference Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 4, no. 4 (2000): 302–12. http://dx.doi.org/10.20965/jaciii.2000.p0302.

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A trajectory tracking experiment system taking an unconstrained table-tennis ball as the control object is constructed, and a fuzzy controller based on the SIRMs dynamically connected fuzzy inference model is proposed. For each of the three input items of the fuzzy controller, a SIRM (Single Input Rule Module) is established and an importance degree is defined. Especially for the input item corresponding to ball velocity, its importance degree is tuned dynamically according to moving conditions. The summation of the products of the importance degree and the fuzzy inference result of the SIRMs

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Shen, Macheng, and Jonathan P. How. "Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning." Proceedings of the International Conference on Automated Planning and Scheduling 31 (May 17, 2021): 578–87. http://dx.doi.org/10.1609/icaps.v31i1.16006.

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This paper studies decision-making in two-player scenarios where the type (e.g. adversary, neutral, or teammate) of the other agent (opponent) is uncertain to the decision-making agent (protagonist), which is an abstraction of security-domain applications. In these settings, the reward for the protagonist agent depends on the type of the opponent, but this is private information known only to the opponent itself, and thus hidden from the protagonist. In contrast, as is often the case, the type of the protagonist agent is assumed to be known to the opponent, and this information-asymmetry signi

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Chiolino, N., A. M. Francis, J. Holmes, M. Barlow, and C. Perkowski. "470 Celsius Packaging System for Silicon Carbide Electronics." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2021, HiTEC (2021): 000083–88. http://dx.doi.org/10.4071/2380-4491.2021.hitec.000083.

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Abstract High temperature Silicon Carbide (SiC) integrated circuit (IC) processes have enabled devices that operate at &gt;450°C for more than a year. These results have established the need for more advanced and practical packaging strategies. Off the shelf state of the art packages cannot withstand the same high temperatures as the semiconductor can for long periods of time. Packaging SiC die to survive temperatures &gt;450°C, while also maintaining a reasonable packaging strategy that is agile, rapid, and modular, presents new challenges. Presented is a technique for packaging SiC d

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Han, Choongyong, Mojdeh Delshad, Kamy Sepehrnoori, and Gary Arnold Pope. "A Fully Implicit, Parallel, Compositional Chemical Flooding Simulator." SPE Journal 12, no. 03 (2007): 322–38. http://dx.doi.org/10.2118/97217-pa.

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Summary A fully implicit, parallel, compositional reservoir simulator has been developed that includes both a cubic equation of state model for the hydrocarbon phase behavior and Hand's rule for the surfactant/oil/brine phase behavior. The aqueous species in the chemical model include surfactant, polymer, and salt. The physical property models include surfactant/oil/brine phase behavior, interfacial tension, viscosity, adsorption, and relative permeability as a function of trapping number. The fully implicit simulation results were validated by comparison with results from our IMPEC chemical f

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Benmakhlouf, Abdeslam, Abdellah Meraoumia, and Mohammed Lakhder Louazene. "Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model." International Journal of Integrated Engineering 15, no. 1 (2023). http://dx.doi.org/10.30880/ijie.2023.15.01.021.

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In this paper, the single input rule modules (SIRMs) dynamically connected fuzzy inference model is employed to design a path following controller for a unicycle wheeled mobile robot(WMR).The SIRMs model is mainly used to reduce the number of fuzzy inference rules and consequently reduce the processing time of the conventional Fuzzy Logic Control (FLC) schemes. The adopted path following strategy uses two control unites working in parallel to drive the WMR to follow a path composed of a succession of discrete waypoints. The first unit is a heading controller charged of generatingthe angular ve

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Hirofumi, Miyajima, Kishida Kazuya, Shigei Noritaka, and Miyajima Hiromi. "Learning Algorithms for Fuzzy Inference Systems Composed of Double- and Single-Input Rule Modules." January 5, 2016. https://doi.org/10.5281/zenodo.1112031.

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pr

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Book chapters on the topic "Single Input Rule Module (SIRM)"

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Zhang, Qiye, and Chunwei Wen. "A Novel Single-Input Rule Module Connected Fuzzy Logic System and Its Applications to Medical Diagnosis." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9682-4_37.

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Conference papers on the topic "Single Input Rule Module (SIRM)"

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Radescu, Radu, and Tudor Ardelean. "E-BUSINESS LEARNING TOOL FOR ONLINE BANKING BASED ON BPM (BUSINESS PROCESS MANAGEMENT)." In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-047.

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Business Process Management (BPM) is a discipline involving any combination of modeling, automation, execution, control, measurement and optimization of business flow. BPM should take into account well-defined input data and a single set of output data. BPM platforms include a portal and a user dashboard, providing concept, simulation, rule definition, process execution, integration, monitoring, and optimization functions. The purpose of this paper is to develop a learning application for the management of banking processes and related databases, which can be used to model the business process

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