Relevant bibliographies by topics / Information Gain Ratio

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Information Gain Ratio'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Information Gain Ratio"

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Dimas, Ari Setyawan. "IMPLEMENTASI FUNGSI DISPERSION RATIO PADA PROSES SPLITING ATRIBUT ALGORITMA DECISION TREE." MADANI: Jurnal Ilmiah Multidisiplin 1, no. 2 (2023): 86–91. https://doi.org/10.5281/zenodo.7782439.

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Metode klasifikasi yang memiliki proses seleksi fitur adalah algoritma decision tree. Proses seleksi fitur pada algortima decision tree biasanya menggunakan fungsi Information Gain. Information gain  pada algoritma decision tree memiliki kelemahan jika ada dataset yang memiliki atribut key seperti Product-ID. Fungsi dispersion ratio pada algoritma decision tree dapat meningkatkan signifikansi proses seleksi fitur, sehingga dapat mengatasi kekurangan fungsi information gain. Proses splitting atribut pada decision tree menggunakan fungsi dispersion ratio dengan menggunakan dataset yang diam
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Ali, Euis Oktavianti, Maria Agustin, and Risna Sari. "IMPLEMENTASI ALGORITMA DECISION TREE DENGAN FITUR SELEKSI WEIGHT BY INFORMATION GAIN." MULTINETICS 9, no. 2 (2024): 118–26. http://dx.doi.org/10.32722/multinetics.v9i2.5715.

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Paper ini bertujuan adalah untuk menerapkan pemilihan bobot fitur dengan mempertimbangkan nilai Gain Ratio pada algoritma Decision Tree dalam mengklasifikasikan nilai akademik mahasiswa. Penentukan pemilihan fitur dari gain ratio berdasarkan informasi nilai split untuk mengurangi bias dalam fitur (atribut). Nilai Gain Ratio tertinggi akan menjadi akar percabangan pada pohon yang menjadi ciri penentu kelulusan mahasiswa. Kami menggunakan 82 data yang dibagi menjadi dua kelas yang disebut lulus dan tidak lulus. Dari data tersebut, diketahui bahwa atribut ip_smt 7 mendapatkan nilai gain ratio ter
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Suprapto, Suprapto. "Improvement Naive Bayes Menggunakan Forward Selection, Information Gain dan Gain Ratio untuk Penanganan Independensi Fitur." Jurnal Sosial Teknologi 5, no. 4 (2025): 925–34. https://doi.org/10.59188/jurnalsostech.v5i4.32084.

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Penelitian ini bertujuan untuk menganalisis peningkatan kinerja algoritma Naive Bayes (NB) dalam menangani independensi fitur menggunakan metode Forward Selection, Information Gain, dan Gain Ratio. Naive Bayes merupakan algoritma klasifikasi yang sering digunakan karena efisiensi komputasinya yang tinggi, namun sering mengalami penurunan performa ketika ada ketergantungan antar fitur. Penelitian ini menggunakan pendekatan eksperimental dengan menerapkan beberapa algoritma, yakni Naive Bayes, Forward Selection Naive Bayes (FSNB), Forward Selection Information Gain Naive Bayes (FSIGNB), dan Forw
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Kurniabudi, Kurniabudi, Abdul Harris, and Albertus Edward Mintaria. "Komparasi Information Gain, Gain Ratio, CFs-Bestfirst dan CFs-PSO Search Terhadap Performa Deteksi Anomali." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 1 (2021): 332. http://dx.doi.org/10.30865/mib.v5i1.2258.

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Large data dimensionality is one of the issues in anomaly detection. One approach used to overcome large data dimensions is feature selection. An effective feature selection technique will produce the most relevant features and can improve the classification algorithm to detect attacks. There have been many studies on feature selection techniques, each using different methods and strategies to find the best and relevant features. In this study, a comparison of Information Gain, Gain Ratio, CFs-BestFirst and CFs-PSO Search techniques was compared. The selection features of the four techniques w
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Mahalingam, P. R., and S. Vivek. "Predicting Financial Savings Decisions Using Sigmoid Function and Information Gain Ratio." Procedia Computer Science 93 (2016): 19–25. http://dx.doi.org/10.1016/j.procs.2016.07.176.

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Dyah, Ayu Kunthi Puspitasari, and Basti Farani Dinesh. "ANALISIS KINERJA PENGAJAR : PENGARUH KEPEMIMPINAN TRANSFORMASIONAL, IKLIM KERJA, DAN KEPUASAN KERJA." MADANI: Jurnal Ilmiah Multidisiplin 1, no. 2 (2023): 92–100. https://doi.org/10.5281/zenodo.7782501.

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Metode klasifikasi yang memiliki proses seleksi fitur adalah algoritma decision tree. Proses seleksi fitur pada algortima decision tree biasanya menggunakan fungsi Information Gain. Information gain  pada algoritma decision tree memiliki kelemahan jika ada dataset yang memiliki atribut key seperti Product-ID. Fungsi dispersion ratio pada algoritma decision tree dapat meningkatkan signifikansi proses seleksi fitur, sehingga dapat mengatasi kekurangan fungsi information gain. Proses splitting atribut pada decision tree menggunakan fungsi dispersion ratio dengan menggunakan dataset yang diam
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Prasetiyo, B., Alamsyah, M. A. Muslim, and N. Baroroh. "Evaluation of feature selection using information gain and gain ratio on bank marketing classification using naïve bayes." Journal of Physics: Conference Series 1918, no. 4 (2021): 042153. http://dx.doi.org/10.1088/1742-6596/1918/4/042153.

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Wang, Zhongzheng, Guangming Deng, and Jianqi Yu. "Group Feature Screening Based on Information Gain Ratio for Ultrahigh-Dimensional Data." Journal of Mathematics 2022 (December 2, 2022): 1–15. http://dx.doi.org/10.1155/2022/1600986.

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Most model-free feature screening approaches focus on the -individual predictor; therefore, they are not able to incorporate structured predictors like grouped variables. In this article, we propose a group screening procedure via the information gain ratio for a classification model, which is a direct extension of the original sure independence screening procedure and also model-free. The proposed method yields a better screening performance and classification accuracy. It is demonstrated that the proposed group screening method possesses the sure screening property and ranking consistency pr
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Azizah, Siti Roziana, Rudy Herteno, Andi Farmadi, Dwi Kartini, and Irwan Budiman. "Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 6 (2023): 1361–68. http://dx.doi.org/10.25126/jtiik.1067467.

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Penyakit jantung menjadi salah satu penyebab utama kematian bersama dengan penyakit lainnya. Dalam bidang teknologi, data mining dapat digunakan untuk mendiagnosa suatu penyakit yang bersumber dari data rekam medis pasien. Pada klasifikasi dataset medis, Naive Bayes merupakan salah satu metode terbaik yang digunakan. Tujuan dari penelitian ini adalah untuk mengetahui perbandingan hasil akurasi dari Naive Bayes menggunakan beberapa seleksi fitur yaitu Forward Selection, Backward Elimination, kombinasi union hasil seleksi fitur Forwad Selection dan Backward Elimination, Information Gain, Gain Ra
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Azizah, Siti Roziana, Rudy Herteno, Andi Farmadi, Dwi Kartini, and Irwan Budiman. "Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 6 (2023): 1361–68. https://doi.org/10.25126/jtiik.2023107467.

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Penyakit jantung menjadi salah satu penyebab utama kematian bersama dengan penyakit lainnya. Dalam bidang teknologi, data mining dapat digunakan untuk mendiagnosa suatu penyakit yang bersumber dari data rekam medis pasien. Pada klasifikasi dataset medis, Naive Bayes merupakan salah satu metode terbaik yang digunakan. Tujuan dari penelitian ini adalah untuk mengetahui perbandingan hasil akurasi dari Naive Bayes menggunakan beberapa seleksi fitur yaitu Forward Selection, Backward Elimination, kombinasi union hasil seleksi fitur Forwad Selection dan Backward Elimination, Information Gain, Gain Ra
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Dissertations / Theses on the topic "Information Gain Ratio"

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Au, Manix. "Automatic State Construction using Decision Trees for Reinforcement Learning Agents." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/15965/1/Manix_Au_Thesis.pdf.

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Reinforcement Learning (RL) is a learning framework in which an agent learns a policy from continual interaction with the environment. A policy is a mapping from states to actions. The agent receives rewards as feedback on the actions performed. The objective of RL is to design autonomous agents to search for the policy that maximizes the expectation of the cumulative reward. When the environment is partially observable, the agent cannot determine the states with certainty. These states are called hidden in the literature. An agent that relies exclusively on the current observations will
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Au, Manix. "Automatic State Construction using Decision Trees for Reinforcement Learning Agents." Queensland University of Technology, 2005. http://eprints.qut.edu.au/15965/.

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Reinforcement Learning (RL) is a learning framework in which an agent learns a policy from continual interaction with the environment. A policy is a mapping from states to actions. The agent receives rewards as feedback on the actions performed. The objective of RL is to design autonomous agents to search for the policy that maximizes the expectation of the cumulative reward. When the environment is partially observable, the agent cannot determine the states with certainty. These states are called hidden in the literature. An agent that relies exclusively on the current observations will not
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Nikjah, Reza. "Performance evaluation and protocol design of fixed-rate and rateless coded relaying networks." Phd thesis, 2010. http://hdl.handle.net/10048/1674.

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The importance of cooperative relaying communication in substituting for, or complementing, multiantenna systems is described, and a brief literature review is presented. Amplify-and-forward (AF) and decode-and-forward (DF) relaying are investigated and compared for a dual-hop relay channel. The optimal strategy, source and relay optimal power allocation, and maximum cooperative gain are determined for the relay channel. It is shown that while DF relaying is preferable to AF relaying for strong source-relay links, AF relaying leads to more gain for strong source-destination or relay-destinatio
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Books on the topic "Information Gain Ratio"

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Inge, M. Thomas, and Dennis Hall. Greenwood Guide to American Popular Culture. Greenwood Publishing Group, Inc., 2002. http://dx.doi.org/10.5040/9798216190752.

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Serious study of popular culture is a fairly recent development, yet scholars in nearly all disciplines now engage with the material culture of the masses. The breadth and depth of coverage in this unique multivolume work make it the most useful reference of its kind currently available. Each essay-length chapter covers a single form, genre, or theme of popular culture, such as comic books, computers, fashion, film, magazines, best-selling books, radio, sports, or TV. Readers and researchers will gain a solid foundation in each subject area, as well as comprehensive information for further res
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Hammond, Andrew. Pop Culture in North Africa and the Middle East. ABC-CLIO, LLC, 2017. http://dx.doi.org/10.5040/9798400698972.

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Ideal for students and general readers, this single-volume work serves as a ready-reference guide to pop culture in countries in North Africa and the Middle East, covering subjects ranging from the latest young adult book craze in Egypt to the hottest movies in Saudi Arabia. Part of the new Pop Culture around the World series, this volume focuses on countries in North Africa and the Middle East, including Algeria, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Saudi Arabia, Syria, the United Arab Emirates, and more. The book enables students to examine the stars, idols, an
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Book chapters on the topic "Information Gain Ratio"

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Han, Tongtong, Wenjing Wang, Min Guo, and Shiyong Ning. "Association Rules Mining Algorithm Based on Information Gain Ratio Attribute Reduction." In Business Intelligence and Information Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92632-8_18.

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Wang, Wenjing, Min Guo, Tongtong Han, and Shiyong Ning. "The Improvement of Attribute Reduction Algorithm Based on Information Gain Ratio in Rough Set Theory." In Business Intelligence and Information Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92632-8_15.

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Sarmah, Sonia, and Sanjib K. Kalita. "A Supervised Band Selection Method for Hyperspectral Images Based on Information Gain Ratio and Clustering." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34872-4_39.

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Cheng, Jian, Botao Jiao, Yinan Guo, and Shijie Wang. "Ensemble Recognition Based on the Harmonic Information Gain Ratio for Unsafe Behaviors in Coal Mines." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78811-7_39.

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Chauhan, Sneha, and Sugata Gangopadhyay. "Design of Intrusion Detection System Based on Logical Analysis of Data (LAD) Using Information Gain Ratio." In Cyber Security, Cryptology, and Machine Learning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07689-3_4.

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Saurer, Matthias, and Steve Voelker. "Intrinsic Water-Use Efficiency Derived from Stable Carbon Isotopes of Tree-Rings." In Stable Isotopes in Tree Rings. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92698-4_17.

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AbstractStable carbon isotopes in tree-rings are not only useful to derive climatic information of the past. Based on the isotope fractionations during uptake and fixation of CO2, physiological information can be retrieved, namely the ratio of assimilation to stomatal conductance, which is termed the intrinsic water-use efficiency (iWUE). This crucial plant physiological trait varies among species and environments and is characteristic of how much water is lost from leaves for a certain carbon gain. iWUE is of great importance at the scale of individual plants because it can determine plant pe
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Heywood, Emma. "Radio, Women IDPs, and Women Journalists." In Palgrave Studies in Communication for Social Change. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35985-9_7.

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AbstractThis final chapter brings together the various threads in the book. It builds on empowerment theories already discussed and intertwines them with concepts of trauma, emotional labour, emotions and affect, and affective proximity by examining humanitarian radio journalism broadcast among internally displaced persons (IDPs) in Burkina Faso and the provision of practical responses to their information needs. It considers how women journalists at a radio studio cover the plight of women IDPs in Burkina Faso and the strategies they have used for the IDP women to gain a voice but also be lis
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Brazdil, Pavel, Jan N. van Rijn, Carlos Soares, and Joaquin Vanschoren. "Dataset Characteristics (Metafeatures)." In Metalearning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67024-5_4.

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SummaryThis chapter discusses dataset characteristics that play a crucial role in many metalearning systems. Typically, they help to restrict the search in a given configuration space. The basic characteristic of the target variable, for instance, determines the choice of the right approach. If it is numeric, it suggests that a suitable regression algorithm should be used, while if it is categorical, a classification algorithm should be used instead. This chapter provides an overview of different types of dataset characteristics, which are sometimes also referred to as metafeatures. These are
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Cao Cungen, Leong Tze-Yun, and Leong Peng Kheong. "Induction of Diagnostic Test Strategies with Multi-Level Information Measures." In Studies in Health Technology and Informatics. IOS Press, 1998. https://doi.org/10.3233/978-1-60750-896-0-477.

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This paper presents a method for inducing clinical diagnostic test protocols or strategies from data. We represent testing strategies as a strategy tree. To support induction of strategy tree, we define three information measures: K-level information, K-level information gain, K-level gain ratio, and K-level cost index, for test selection during strategy building. These measures generalize Quinlan's information measures used in decision tree induction. We present theoretical and experimental results to show that the K-level cost index can be used to induce strategy trees in a practica
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Xie Yang, Khanna Sankalp, Good Norm, and Boyle Justin. "Weekly Hospital Workforce Data: A Data Visualisation Exercise." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-783-2-153.

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Quantifying the health workforce in terms of overall staff numbers and their ratio to patients under their care can strengthen analytical studies designed to inform policy regarding how hospital services are delivered. Information about staffing is traditionally obtained via location-specific audits or self-reported information gleaned from surveys which hold potential biases around time-dependence and recall. In contrast, work presented in this paper describes the derivation of useful workforce metrics from routine hospital financial and clinical information systems that overcome these biases
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Conference papers on the topic "Information Gain Ratio"

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Ma, Benhua, Dewei Zhang, Hailin Deng, and Dalong Lv. "Radio Frequency Analog predistortion linearizer with independently tunable gain and adjustable inflection depth for Ku-Band TWTA." In 2024 4th International Conference on Electronics, Circuits and Information Engineering (ECIE). IEEE, 2024. http://dx.doi.org/10.1109/ecie61885.2024.10626816.

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Shishkin, Mikhail S. "Aperture Efficiency Improvement Methods Analysis for High-Gain Wideband/Ultrawideband Stacked Microstrip Antennas." In 2024 IEEE 3rd International Conference on Problems of Informatics, Electronics and Radio Engineering (PIERE). IEEE, 2024. https://doi.org/10.1109/piere62470.2024.10804914.

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Mori, Tatsunori. "Information gain ratio as term weight." In the 19th international conference. Association for Computational Linguistics, 2002. http://dx.doi.org/10.3115/1072228.1072246.

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Chen, Jiazheng, Jingjing Hu, and Gangqiang Zhang. "Feature Selection Based on Gain Ratio in Hybrid Incomplete Information Systems." In 2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE, 2021. http://dx.doi.org/10.1109/iske54062.2021.9755425.

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Chung-Pi Lee and Hsuan-Jung Su. "Diversity-multiplexing gain tradeoff with peak to average power ratio constraints." In 2008 42nd Annual Conference on Information Sciences and Systems (CISS). IEEE, 2008. http://dx.doi.org/10.1109/ciss.2008.4558646.

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Xia, Yan, Jian Shu, Na Xu, and Hui Feng. "Discipline Decision Tree Classification Algorithm and Application based on Weighted Information Gain Ratio." In 8th International Conference on Computer Supported Education. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005748000770084.

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Ren, Wei, Yepeng Qiu, and Xianghua Li. "An Information Gain Ratio based Discovery of User Similarity in Sina Blog Community." In ACAI 2018: 2018 International Conference on Algorithms, Computing and Artificial Intelligence. ACM, 2018. http://dx.doi.org/10.1145/3302425.3302449.

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Li, Shenggang, Wenli Shang, Chunyu Chen, Yan Lu, Zhiwei Dong, and Ye Xu. "Security monitoring method for ICS based on information gain ratio and maximum entropy model." In 2020 Chinese Automation Congress (CAC). IEEE, 2020. http://dx.doi.org/10.1109/cac51589.2020.9327281.

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Triwiyatno, Aris, Budi Setiyono, Joshua Harbangan Dharmarakel Panjaitan, Andra Kurniahadi, and Iwan Setiawan. "Design of Air-Fuel Ratio Control Using Gain- Scheduled Fuzzy-PID for Small Scooter Engine." In 2020 7th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE). IEEE, 2020. http://dx.doi.org/10.1109/icitacee50144.2020.9239240.

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Hu, S. D., H. Li, and H. S. Tzou. "Optimal Control of Piezoelectric Laminated Parabolic Cylindrical Panels." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12513.

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Vibration control of parabolic cylindrical shell panels by piezoelectric patches using optimal control algorithm is presented in this study. Laminated piezoelectric patches serve as distributed sensors and actuators. Dynamic behaviors and mode shape functions in three directions are obtained by the Rayleith-Ritz method. The sensing sensitivity of the piezoelectric sensor and the actuation force of the piezoelectric actuator are obtained. Feedback control gain between sensing and control signals is solved using the LQ optimal control algorithm. LQ controllers for independent modes are designed,
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Reports on the topic "Information Gain Ratio"

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Miles, Gaines E., Yael Edan, F. Tom Turpin, et al. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570567.bard.

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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were st
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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the proj
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