Relevant bibliographies by topics / Mamdani Fuzzy system

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Academic literature on the topic 'Mamdani Fuzzy system'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Mamdani Fuzzy system"

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Elfaladonna, Febie, and Indra Griha Tofik Isa. "UJI EFEKTIFITAS METODE FUZZY LOGIC MAMDANI PADA PENERIMAAN BEASISWA BANTUAN MENGGUNAKAN MATLAB." SINTECH (Science and Information Technology) Journal 5, no. 1 (2022): 75–86. http://dx.doi.org/10.31598/sintechjournal.v5i1.1043.

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One of the supporters in creating an even educational climate is the existence of scholarships. In general, scholarships in the form of financial assistance intended for the community of higher education, both lecturers, teachers, students and students. In the awarding of scholarships, some findings were obtained, including not being on target which caused the scholarship assistance to be ineffective. One solution in determining the acceptance of scholarships is the existence of a system that is integrated with decision-making methods. Fuzzy logic mamdani becomes one of the recommendation meth
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Istiadi, Istiadi, Emma Budi Sulistiarini, Rudy Joegijantoro, Anik Vega Vitianingsih, and Affi Nizar Suksmawati. "Mamdani Fuzzy Expert System for Online Learning to Diagnose Infectious Diseases." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 6 (2022): 1047–56. http://dx.doi.org/10.29207/resti.v6i6.4656.

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E-learning and expert systems can be implemented for learning in the health sector. Through the e-learning system, prospective health workers can analyze problems by exploring the material in the system. However, material learning alone is less effective, so case study-based learning using an expert system is needed to strengthen understanding. The research applies an expert system to online learning to diagnose several infectious diseases. The disease diagnosis process uses the backward chaining method and the Mamdani fuzzy inference system. The fuzzy Mamdani inference system determines the i
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E. Kizito, Anazia, Emmanuel Ojei, and M. D. Okpor. "A Fuzzy Logic-Based Automobile Fault Detection System Using Mamdani Algorithm." International Journal of Scientific Research and Management (IJSRM) 12, no. 03 (2024): 1081–93. http://dx.doi.org/10.18535/ijsrm/v12i03.ec06.

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Due to advancement and complexity of modern automobiles, fault detection has gone beyond manual or trial by error methods. The fault detection technologies in automotive industry is used to identify any potential or already existing fault in automobiles. Faults in automobiles are usually mechanical or electrical faults that may include airbag control unit, radiator, gearbox, transmission control unit, tyre pressure, brakes, air conditioner, cylinder casket, alternator, hubs malfunctions etc. Each fault has a specific or related sign and symptoms. There are several methods of fault detections i
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Borroek, Maria Rosario, Errissya Rasywir, and Yovi Pratama. "Pengukuran Perangkat Lunak Untuk Effort Estimation Dengan Teknik Pembelajaran Mesin." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 2 (2020): 445. http://dx.doi.org/10.30865/mib.v4i2.2083.

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Software effort estimation is to estimate the amount of resources needed in developing the software. For that software effort estimation is important so need to see the effect of software measurement to software effort estimation which is done by machine learning technique. Based on this the researcher tries to build a system capable of measuring software. In this study experiments on software measurement techniques (FPA, FPA with Sugeno fuzzy and FPA with mamdani fuzzy). The three types of techniques are compared with the three project data for further software effort estimation. For evaluati
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Wanti, Linda Perdana, Oman Somantri, Nur Wachid Adi Prasetya, and Lina Puspitasari. "Fuzzy expert system design for detecting stunting." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 1 (2024): 556. http://dx.doi.org/10.11591/ijeecs.v34.i1.pp556-564.

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Stunting is a chronic nutritional problem that occurs in toddler due to lack of nutritional intake which results in impaired growth toddler. Usually, toddler who experience stunting are characterized by not increasing weight over a long period of time. Application utilization health which makes it easier for users to access information, one of which can be used to identify toddler who are stunted by selecting symptoms. The symptoms experienced by toddlers go through a system known as the system expert. In this research an expert system will be developed that is capable of early detection devel
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Wanti, Linda Perdana, Oman Somantri, Nur Wachid Adi Prasetya, and Lina Puspitasari. "Fuzzy expert system design for detecting stunting." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 1 (2024): 556–64. https://doi.org/10.11591/ijeecs.v34.i1.pp556-564.

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Stunting is a chronic nutritional problem that occurs in toddler due to lack of nutritional intake which results in impaired growth toddler. Usually, toddler who experience stunting are characterized by not increasing weight over a long period of time. Application utilization health which makes it easier for users to access information, one of which can be used to identify toddler who are stunted by selecting symptoms. The symptoms experienced by toddlers go through a system known as the system expert. In this research an expert system will be developed that is capable of early detection devel
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Marbun, Murni, Sandhuri -, and Aishwarya -. "Analysis of Application of Fuzzy Grid Partition on Mamdani Method Fuzzy Inference System." Jurnal Sistem Informasi dan Ilmu Komputer Prima(JUSIKOM PRIMA) 6, no. 1 (2022): 68–74. http://dx.doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2890.

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The Mamdani method has been widely used for various control devices, which is the beginning of fuzzy technology and has the advantage of being able to express concepts that are difficult to formulate and the use of fuzzy membership functions in making objective observations of subjective values, making it easier to make decisions that are full of uncertainty. The Mamdani method has also been widely used for various optimization problems. This study produces new findings on the analysis of the application of fuzzy grid partition on the fuzzy inference system of the Mamdani method for the issue
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Harliana, Putri, Mardiana Mardiana, and Yuris Agustira Nainggolan. "Analisa Perbandingan Tingkat Akurasi dalam Memprediksi Laju Inflasi Kota Medan Menggunakan Model Fuzzy Inference System Sugeno dan Mamdani." Hello World Jurnal Ilmu Komputer 1, no. 3 (2022): 145–52. http://dx.doi.org/10.56211/helloworld.v1i3.130.

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Logika fuzzy merupakan perluasan dari penalaran tradisional, di mana x adalah salah satu anggota dari himpunan A atau tidak, atau sebuah x dapat menjadi anggota himpunan A dengan derajat keanggotaan (μ) tertentu. Kemampuan model fuzzy dalam memetakan nilai kabur menjadi alasan penggunaan model inferensi fuzzy dalam berbagai kasus yang menggunakan nilai kabur untuk menghasilkan suatu output yang jelas atau pasti. Dalam penelitian ini akan dilakukan analis tingkat akurasi yang dihasilkan model inferensi fuzzy Sugeno dan Mamdani dalam memprediksi laju inflasi di Kota Medan, hasil prediksi akan di
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Darmawati, Darmawati. "Proses Pendiagnosaan Penyakit Menggunakan Logika Fuzzy Dengan Metode Mamdani." SAINTIFIK 3, no. 2 (2017): 161–70. http://dx.doi.org/10.31605/saintifik.v3i2.156.

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Logika fuzzy merupakan cabang dari logika klasik. Logika fuzzy lahir setelah logika klasik dianggap terlalu eksak untuk masalah nyata yang terkadang begitu kompleks. Salah satunya adalah proses pendiagnosaan penyakit, yang menjadi hal penting dan mendasar dalam kedokteran. Hal ini disebabkan pengambilan tindakan terapi dan pengobatannya berdasarkan pada hasil diagnosa itu. Dengan bantuan Fuzzy Expert System (FES) pada metode Mamdani, dapat diperoleh hasil perkiraan diagnosa untuk seorang pasien terhadap suatu penyakit dengan memperhatikan gejala penyakit tersebut. Metode Mamdani mempunyai empa
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Rezky Aprilianto, Arif, Budi Cahyono, and Mohamad Tafrikan. "Implementation of Mamdani Method Fuzzy System in Determining Final Semester Grades of UIN Walisongo Semarang Students." Contemporary Mathematics and Applications (ConMathA) 7, no. 1 (2025): 46–63. https://doi.org/10.20473/conmatha.v7i1.53479.

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Final semester grades are an important component for students to obtain a pass in completing a course. The program for determining final semester grades using fuzzy Mamdani can be used to facilitate the calculation of final semester grades. This research aims to determine the results of applying the Mamdani fuzzy system method in determining the final semester grades of students at UIN Walisongo Semarang. The Mamdani fuzzy system method was chosen as the method for calculating final semester grades along with MAPE (Mean Absolute Percentage Error) calculations. In accordance with the lecture co
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Dissertations / Theses on the topic "Mamdani Fuzzy system"

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Tan, Lujiao. "Takagi-Sugeno and Mamdani Fuzzy Control of a Resort Management System." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2661.

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By means of fuzzy set theory as well as Takagi-Sugeno and Mamdani fuzzy controller, this paper presents the investigation of a Resort Management System implemented by a combination of a T-S model and a Mamdani model. It demonstrates the procedure of the specific premise parameters identification and consequence parameters identification performed by regression knowledge in the T-S model, and the process of the fuzzification, the rule base creation and the defuzzification with COG technique in the Mamdani model. Therefore, an aggregation between T-S controller and Mamdani controller applied in
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Karimov, Azar. "Office Rent Variation In Istanbul Cbd: An Application Of Mamdani And Tsk-type Fuzzy Rule Based System." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612322/index.pdf.

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Over the past decade, fuzzy systems have gained remarkable acceptance in many fields including control and automation, pattern recognition, medical diagnosis and forecasting. The fuzzy system application has also been accepted as a promising approach to dealing with uncertainty in real estate valuation analysis. This is mainly due to the necessity of coping with a large number of qualitative and quantitative variables that affect the value of a real property. The appraisers use a great deal of judgment to identify both the characteristics that contribute to property values and the relationsh
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Zettervall, Hang. "Fuzzy Set Theory Applied to Make Medical Prognoses for Cancer Patients." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Engineering - Department of Mathematics and Natural Sciences, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00574.

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As we all know the classical set theory has a deep-rooted influence in the traditional mathematics. According to the two-valued logic, an element can belong to a set or cannot. In the former case, the element’s membership degree will be assigned to one, whereas in the latter case it takes the zero value. With other words, a feeling of imprecision or fuzziness in the two-valued logic does not exist. With the rapid development of science and technology, more and more scientists have gradually come to realize the vital importance of the multi-valued logic. Thus, in 1965, Professor Lotfi A. Zadeh
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García, Z. Yohn E. "Fuzzy logic in process control: A new fuzzy logic controller and an improved fuzzy-internal model controller." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/2529.

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Two fuzzy controllers are presented. A fuzzy controller with intermediate variable designed for cascade control purposes is presented as the FCIV controller. An intermediate variable and a new set of fuzzy logic rules are added to a conventional Fuzzy Logic Controller (FLC) to build the Fuzzy Controller with Intermediate Variable (FCIV). The new controller was tested in the control of a nonlinear chemical process, and its performance was compared to several other controllers. The FCIV shows the best control performance regarding stability and robustness. The new controller also has an acceptab
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Chatterjee, D. "Prediction of Multi Responses in Radial Drilling Process using Mamdani Fuzzy Inference System." Thesis, 2010. http://ethesis.nitrkl.ac.in/1687/1/Debraj_Final_thesis.pdf.

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Engineering problems often embody many characteristics of a multi-response optimization problem, and these responses are often conflicting in nature. To address this issue, the present work uses Grey- based Taguchi method to express surface roughness of drilled holes and drill flank wear into an equivalent single response grey relational grade. Experiments have been conducted in a radial drilling machine with five input parameters using L27 orthogonal array. It has been observed that combined response of flank wear and surface roughness is affected by almost all input parameters; however, dril
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Book chapters on the topic "Mamdani Fuzzy system"

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Verma, Nishchal K., Vikas Singh, Shreedharkumar Rajurkar, and Mohd Aqib. "Fuzzy Inference Network with Mamdani Fuzzy Inference System." In Computational Intelligence: Theories, Applications and Future Directions - Volume I. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1132-1_29.

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Maia, Daniel Helder, and Arjab Singh Khuman. "A Mamdani Fuzzy Logic Inference System to Estimate Project Cost." In Fuzzy Logic. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66474-9_10.

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Hughes, Sophie, and Arjab Singh Khuman. "Automatic Camera Flash Using a Mamdani Type One Fuzzy Inference System." In Fuzzy Logic. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66474-9_13.

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Bede, Barnabas, and Imre J. Rudas. "Takagi-Sugeno Approximation of a Mamdani Fuzzy System." In Advance Trends in Soft Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03674-8_28.

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Chmielowski, Wojciech Z. "A System Controlling Liquid Temperature Using Mamdani Fuzzy Controllers (SIMO)." In Fuzzy Control in Environmental Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19261-1_7.

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Mohamed, Siti Rosiah, Fairuz Shohaimay, Nazirah Ramli, Nazihah Ismail, and Syafiza Saila Samsudin. "Academic Poster Evaluation by Mamdani-Type Fuzzy Inference System." In Regional Conference on Science, Technology and Social Sciences (RCSTSS 2016). Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0074-5_85.

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Putri, Salsabila Naura. "Application of Fuzzy Inference System Mamdani at Pelican Crossing." In Proceedings of the 5th International Conference on Rehabilitation and Maintenance in Civil Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9348-9_60.

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Mittal, Usha, Sayantan Kar, and Priyanka Chawla. "COVID-19 detection through Mamdani-based fuzzy inference system." In Artificial Intelligence and Speech Technology. CRC Press, 2021. http://dx.doi.org/10.1201/9781003150664-41.

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Yaguinuma, Cristiane A., Walter C. P. Magalhães, Marilde T. P. Santos, Heloisa A. Camargo, and Marek Reformat. "Combining Fuzzy Ontology Reasoning and Mamdani Fuzzy Inference System with HyFOM Reasoner." In Enterprise Information Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09492-2_11.

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Musayev, Akif, Shahzade Madatova, and Samir Rustamov. "Mamdani-Type Fuzzy Inference System for Evaluation of Tax Potential." In Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75408-6_39.

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Conference papers on the topic "Mamdani Fuzzy system"

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Priya and Neha Gupta. "Fuzzy based Mamdani Inference System for Botnet Detection." In 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET). IEEE, 2024. http://dx.doi.org/10.1109/acet61898.2024.10730059.

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Tuly, Tanjina Ahmed, Tanjid Ahammed Shafin, Md Zahid Hasan, Md Hasan Imam Bijoy, Mohammad Shamsul Arefin, and Mohammad Shorif Uddin. "A Mamdani Fuzzy Inference System for Comprehensive Diabetes Risk Evaluation." In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 2025. https://doi.org/10.1109/ecce64574.2025.11013995.

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Cahyanto, Triawan Adi, Genta Sufianto, Luluk Handayani, Ulya Anisatur Rosyidah, Rosita Yanuarti, and Yusril Izzi Arlisa Amiri. "IoT-Based Recommendation System for Citrus Land Suitability Using Mamdani Fuzzy Logic." In 2024 Beyond Technology Summit on Informatics International Conference (BTS-I2C). IEEE, 2024. https://doi.org/10.1109/bts-i2c63534.2024.10941761.

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Fahmi, Monika Faswia, Deni Tri Laksono, Vivi Tri Widyaningrum, Malik Luqmanul Hakim, Arsy Aryasafa P., and Dedi Tri Laksono. "Design of Soil Fertility Detection System Using Fuzzy Mamdani Method based on GIS Site Mapping." In 2024 Beyond Technology Summit on Informatics International Conference (BTS-I2C). IEEE, 2024. https://doi.org/10.1109/bts-i2c63534.2024.10942161.

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Selamat, Ali, Mohd Aizaini Maarof, and Tey Yi Chin. "Fuzzy Mamdani Inference System Skin Detection." In 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.224.

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Arnett, Timothy, Kelly Cohen, Matthew Clark, David W. Casbeer, and Kuldip Rattan. "Transformation of a hierarchical mamdani fuzzy system to a single fuzzy system representation." In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015597.

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Mastacan, Lucian, and Constantin-Catalin Dosoftei. "Temperature Fuzzy Control System with Mamdani Controller." In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE). IEEE, 2018. http://dx.doi.org/10.1109/icepe.2018.8559861.

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Alves, Kaike, Rosangela Ballini, and Eduardo Aguiar. "A New Fuzzy Inference System Applied to Time Series Forecasting." In Congresso Brasileiro de Inteligência Computacional. SBIC, 2023. http://dx.doi.org/10.21528/cbic2023-003.

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Fuzzy systems are a class of machine learning introduced by Zadeh that combine accuracy and interpretability. This class of models consists of two main parts, the antecedent and the consequent. While the antecedent is responsible for modeling the inputs, the consequent concerns modeling the output. The literature reports two main types of fuzzy systems: Mamadani and Takagi-Sugeno. While Mamdani uses fuzzy sets in the consequent part, Takagi-Sugeno uses polynomial functions. Consequently, Mamdani provides better understandable models and Takagi-Sugeno more accurate ones. In this paper, we propo
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Tupinambas, Taiguara Melo, Rafael Aeraf Leao Cadence, and Andre Paim Lemos. "Cryptocurrencies Transactions Advisor Using a Genetic Mamdani-type Fuzzy Rules Based System." In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2018. http://dx.doi.org/10.1109/fuzz-ieee.2018.8491619.

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Khan, M. K. A. Ahamed, Razif Rashid, I. Elamvazuthi, Nader Barsoum, Jeffrey Frank Webb, and Pandian Vasant. "MAMDANI FUZZY SYSTEM FOR INDOOR AUTONOMOUS MOBILE ROBOT." In PROCEEDINGS OF THE FOURTH GLOBAL CONFERENCE ON POWER CONTROL AND OPTIMIZATION. AIP, 2011. http://dx.doi.org/10.1063/1.3592449.

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