Relevant bibliographies by topics / Decision Based Algorithm

Contents

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

Academic literature on the topic 'Decision Based Algorithm'

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

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Journal articles on the topic "Decision Based Algorithm"

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Singh, Surya Partap, Amitesh Srivastava, Suryansh Dwivedi, and Mr Anil Kumar Pandey. "AI Based Recruitment Tool." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2815–19. http://dx.doi.org/10.22214/ijraset.2023.52193.

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Abstract: In this study, the researchers narrowed their focus to the application of algorithmic decision-making in ranking job applicants. Instead of comparing algorithms to human decision-makers, the study examined participants' perceptions of different types of algorithms. The researchers varied the complexity and transparency of the algorithm to understand how these factors influenced participants' perceptions. The study explored participants' trust in the algorithm's decision-making abilities, fairness of the decisions, and emotional responses to the situation. Unlike previous work, the st
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Feng, Guoxu, Songbo Gu, and Shihu Sun. "Intelligent Ship Collision Avoidance Support System Based on the Algorithm of Anthropomorphic Physics." International Journal of Ambient Computing and Intelligence 15, no. 1 (2024): 1–20. https://doi.org/10.4018/ijaci.365340.

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Most of the collision-related decisions of ships at sea depend on the working experience of drivers and determining a reasonable avoidance decision quickly when facing a multivessel encounter situation is difficult, so applying intelligent algorithms to assist these decisions is necessary. On the basis of this, the authors researched the construction of intelligent decision support systems for ship collision avoidance that relies on an anthropomorphic physics optimization algorithm. They used this algorithm to obtain the global range optimal solutions through iteration, which provides effectiv
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Ma, Xiuqin, Yanan Wang, Hongwu Qin, and Jin Wang. "A Decision-Making Algorithm Based on the Average Table and Antitheses Table for Interval-Valued Fuzzy Soft Set." Symmetry 12, no. 7 (2020): 1131. http://dx.doi.org/10.3390/sym12071131.

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Interval-valued fuzzy soft set is one efficient mathematical model employed to handle the uncertainty of data. At present, there exist two interval-valued fuzzy soft set-based decision-making algorithms. However, the two existing algorithms are not applicable in some cases. Therefore, for the purpose of working out this problem, we propose a new decision-making algorithm, based on the average table and the antitheses table, for this mathematical model. Here, the antitheses table has symmetry between the objects. At the same time, an example is designed to prove the availability of our algorith
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VUKIĆEVIĆ, MILAN, MILOŠ JOVANOVIĆ, BORIS DELIBAŠIĆ, SONJA IŠLJAMOVIĆ, and MILIJA SUKNOVIĆ. "REUSABLE COMPONENT-BASED ARCHITECTURE FOR DECISION TREE ALGORITHM DESIGN." International Journal on Artificial Intelligence Tools 21, no. 05 (2012): 1250022. http://dx.doi.org/10.1142/s0218213012500224.

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Many decision tree algorithms were proposed over the last few decades. A lack of publishing standards for decision tree algorithm software produced a large time gap between algorithm proposals and their wider application in practice. Non-existence of common repository for storing algorithms and their parts led to a need to re-implement these algorithms from a scratch when they had to be implemented on a different platform. This makes the comparison between algorithms and their partial improvements vague. In addition, combinations and interactions between different algorithm parts haven't been
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Shakya, Subarna. "Probabilistic Neural Network based Managing Algorithm for Building Automation System." December 2021 3, no. 4 (2021): 272–83. http://dx.doi.org/10.36548/jaicn.2021.4.001.

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A building automation system is a centralized intelligent system, which controls the operation of energy, security, water, and safety by the help of hardware and software modules. The general software modules employed for automation process have an algorithm with pre-determined decisions. However, such pre-determined decision algorithms won’t work in a proper manner at all situations like a human brain. Therefore a human biological inspired algorithms are developed in recent days and termed as neural network algorithms. The Probabilistic Neural Network (PNN) is a kind of artificial neural netw
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EL-GHAMRAWY, SALLY M., and ALI I. ELDESOUKY. "AN AGENT DECISION SUPPORT MODULE BASED ON GRANULAR ROUGH MODEL." International Journal of Information Technology & Decision Making 11, no. 04 (2012): 793–820. http://dx.doi.org/10.1142/s0219622012500216.

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A multi-agent system (MAS) is a branch of distributed artificial intelligence, composed of a number of distributed and autonomous agents. In a MAS, effective coordination is essential for autonomous agents to achieve their goals. Any decision based on a foundation of knowledge and reasoning can lead agents into successful cooperation; to achieve the necessary degree of flexibility in coordination, an agent must decide when to coordinate and which coordination mechanism to use. The performance of any MAS depends directly on the decisions made by the agents. The agents must therefore be able to
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Pan, Yunfei, Hongyong Jia, Wenhe Liu, He Sun, Mingyang Xu, and Cen Chen. "Mimicry API Gateway Decision Algorithm Based on Trust Distribution." Journal of Physics: Conference Series 2424, no. 1 (2023): 012004. http://dx.doi.org/10.1088/1742-6596/2424/1/012004.

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Abstract Aiming at the lack of dynamic and comprehensiveness of trust evaluation methods in current adjudication algorithms, an adjudication algorithm for mimic API gateway based on trust distribution is proposed. The algorithm comprehensively considers the direct and indirect trust relationships between equipment executives from the perspective of trust distribution, and on this basis introduces a dynamic penalty strategy, which greatly improves the dynamics and effectiveness of the algorithm. In addition, the algorithm is simulated and tested in the simulated API gateway environment, and the
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Guo, Jinlin, Haoran Wang, Xinwei Li, and Li Zhang. "Stream Classification Algorithm Based on Decision Tree." Mobile Information Systems 2021 (December 21, 2021): 1–11. http://dx.doi.org/10.1155/2021/3103053.

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Due to the rise of many fields such as e-commerce platforms, a large number of stream data has emerged. The incomplete labeling problem and concept drift problem of these data pose a huge challenge to the existing stream data classification methods. In this respect, a dynamic stream data classification algorithm is proposed for the stream data. For the incomplete labeling problem, this method introduces randomization and iterative strategy based on the very fast decision tree VFDT algorithm to design an iterative integration algorithm, and the algorithm uses the previous model classification r
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Kašćelan, Ljiljana, and Vladimir Kašćelan. "Component-Based Decision Trees." International Journal of Operations Research and Information Systems 6, no. 4 (2015): 1–18. http://dx.doi.org/10.4018/ijoris.2015100101.

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Popular decision tree (DT) algorithms such as ID3, C4.5, CART, CHAID and QUEST may have different results using same data set. They consist of components which have similar functionalities. These components implemented on different ways and they have different performance. The best way to get an optimal DT for a data set is one that use component-based design, which enables user to intelligently select in advance implemented components well suited to specific data set. In this article the authors proposed component-based design of the optimal DT for classification of securities account holders
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Sirajuddin Hawari, Muhammad Zulfikri Maulanab, Teuku Binzar Nawaf Musyaffa, Desy Komalasari, and Mutiara Persada Pulungan. "MINIMAX ALGORITHM BASED ON "MAIN INI YUK" GAME." Jurnal ilmiah Sistem Informasi dan Ilmu Komputer 2, no. 1 (2022): 12–17. http://dx.doi.org/10.55606/juisik.v2i1.318.

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In the game there are rules for each game. The rules are made as a challenge to achieve victory. To achieve victory requires analysis of the right algorithm in making decisions. Minimax is one of the best decision-making algorithms to be applied in a game. The time complexity of the minimax algorithm is O(b^m) which b is the branching and m is the depth.
 
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Dissertations / Theses on the topic "Decision Based Algorithm"

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Manongga, D. H. F. "Using genetic algorithm-based methods for financial analysis." Thesis, University of East Anglia, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320950.

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Sun, Chi. "A constrained MDP-based vertical handoff decision algorithm for wireless networks." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/1243.

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The 4th generation wireless communication systems aim to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. To achieve this goal, the support of vertical handoff is important in mobility management. This thesis focuses on the vertical handoff decision algorithm, which determines the criteria under which vertical handoff should be performed. The problem is formulated as a constrained Markov decision process. The objective is to maximize the expected total reward of a connection subject to the expected total access cost constraint. In our model,
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Tobin, Ludovic. "A Stochastic Point-Based Algorithm for Partially Observable Markov Decision Processes." Thesis, Université Laval, 2008. http://www.theses.ulaval.ca/2008/25194/25194.pdf.

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La prise de décision dans un environnement partiellement observable est un sujet d'actualité en intelligence artificielle. Une façon d'aborder ce type de problème est d'utiliser un modèle mathématique. Notamment, les POMDPs (Partially Observable Markov Decision Process) ont fait l'objet de plusieurs recherches au cours des dernières années. Par contre, résoudre un POMDP est un problème très complexe et pour cette raison, le modèle n'a pas été utilisé abondamment. Notre objectif était de continuer les progrès ayant été réalisé lors des dernières années, avec l'espoir que nos travaux de recherch
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Trivedi, Ankit P. "Decision tree-based machine learning algorithm for in-node vehicle classification." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10196455.

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<p> This paper proposes an in-node microprocessor-based vehicle classification approach to analyze and determine the types of vehicles passing over a 3-axis magnetometer sensor. The approach for vehicle classification utilizes J48 classification algorithm implemented in Weka (a machine learning software suite). J48 is Quinlan's C4.5 algorithm, an extension of decision tree machine learning based on an ID3 algorithm. The decision tree model is generated from a set of features extracted from vehicles passing over the 3-axis sensor. The features are attributes provided with correct classification
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Bacak, Hikmet Ozge. "Decision Making System Algorithm On Menopause Data Set." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12612471/index.pdf.

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Multiple-centered clustering method and decision making system algorithm on menopause data set depending on multiple-centered clustering are described in this study. This method consists of two stages. At the first stage, fuzzy C-means (FCM) clustering algorithm is applied on the data set under consideration with a high number of cluster centers. As the output of FCM, cluster centers and membership function values for each data member is calculated. At the second stage, original cluster centers obtained in the first stage are merged till the new numbers of clusters are reached. Merging process
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Skipper, Lee R. "Development of a microcomputer-based capital budgeting algorithm for the dynamic decision environment." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/101266.

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The capital budgeting process is conducted in a dynamic, uncertain environment. In each period of the process, a manager has only estimated values for system parameters, project costs, and project returns. The manager must consider project firm's capital among interdependencies the available in allocating the projects. After completing the allocation process in one period, the chosen projects are funded until the end of the next period. These projects are then considered along with new projects and the process is repeated again. The capital budgeting decision in one period is therefore only on
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Artita, Kimberly. "Computer-based decision-support methods for hydrological ecosystem services management." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/dissertations/530.

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Changing climates, human population growth, and aging infrastructure threaten the availability and quality of one of life's most vital resources, water. Hydrological ecosystem services are goods and benefits derived from freshwater that include flood damage mitigation, water for agricultural and commercial use, swimmable and navigable waters, and healthy aquatic habitats. Using computer algorithms inspired by biological and ecological processes known as evolutionary algorithms and on-site stormwater management practices such structural best management practices (BMPs) and green stormwater infr
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Abdul, Manaf Norhuda. "MANAGEMENT DECISION SUPPORT SYSTEM OF SOLVENT-BASED POST-COMBUSTION CARBON CAPTURE." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16567.

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A management decision-support framework for a coal-fired power plant with solvent based post combustion CO2 capture (PCC) (integrated plant) is proposed and developed in this thesis. A brief introduction pertaining to the solvent-based PCC technology, thesis motivations and objectives are given in Chapter 1. Chapter 2 comprises a comprehensive literature review of solvent-based PCC plant from the bottom level (PCC instrumentation level) until the top level (managerial decision of PCC system). Chapter 3 describes the development of solvent-based PCC dynamic model via empirical methods. Open-
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Ghasemzadeh, Mohammad. "A new algorithm for the quantified satisfiability problem, based on zero-suppressed binary decision diagrams and memoization." Phd thesis, [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=978444213.

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Parandekar, Amey V. "Development of a Decision Support Framework forIntegrated Watershed Water Quality Management and a Generic Genetic Algorithm Based Optimizer." NCSU, 1999. http://www.lib.ncsu.edu/theses/available/etd-19990822-032656.

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<p>PARANDEKAR, AMEY, VIJAY. Development of a Decision Support Framework for Integrated Watershed Water Quality Management and a Generic Genetic Algorithm Based Optimizer. (Under the direction of Dr. S. Ranji Ranjithan.)The watershed management approach is a framework for addressing water quality problems at a watershed scale in an integrated manner that considers many conflicting issues including cost, environmental impact and equity in evaluating alternative control strategies. This framework enhances the capabilities of current environmental analysis frameworks by the inclusion of additional
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Books on the topic "Decision Based Algorithm"

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Chang, Hyeong Soo. Simulation-Based Algorithms for Markov Decision Processes. 2nd ed. Springer London, 2013.

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Chang, Hyeong Soo, Jiaqiao Hu, Michael C. Fu, and Steven I. Marcus. Simulation-based Algorithms for Markov Decision Processes. Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-690-2.

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Chang, Hyeong Soo, Jiaqiao Hu, Michael C. Fu, and Steven I. Marcus. Simulation-Based Algorithms for Markov Decision Processes. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5022-0.

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Soo, Chang Hyeong, ed. Simulation-based algorithms for Markov decision processes. Springer, 2007.

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K, Krzeczowski, American Institute of Aeronautics and Astronautics., and United States. National Aeronautics and Space Administration., eds. Knowledge-based scheduling of arrival aircraft. American Institute of Aeronautics and Astronautics, 1995.

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Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.

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The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee.&#x0D; The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledg
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Albrecht, Eduardo. Political Automation. Oxford University Press, 2025. https://doi.org/10.1093/9780197696989.001.0001.

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Abstract Governments, once staffed exclusively with human bureaucrats, now routinely use AI-based software to gather information about citizens and make decisions that impact their lives. In many nations, AI determines the level of privacy a person can enjoy, how far they can travel, what public benefits they may receive, and what they can and cannot say publicly. This amounts to a phenomenon of political automation rapidly materializing globally and begs the question: What input do citizens have in how these machines think? The book explores this question in various domains—including policing
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Varlamov, Oleg. Mivar databases and rules. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in th
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Varlamov, Oleg. 18 examples of mivar expert systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1248446.

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Many years of research on mivar technologies of logical artificial intelligence have allowed us to create a new powerful, versatile and fast tool, which is called "multidimensional open gnoseological active net" — "multidimensional open gnoseological active net: MOGAN". This tool allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format, and it can be used to model cause-and-effect relationships in different subject areas and create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert system
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Kochetova, Zhanna, Natal'ya Maslova, and Oleg Bazarskiy. Aviation and missile clusters and the environment. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1544137.

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The monograph introduces a new concept - the aviation and missile cluster as a new class of objects of geo-ecological monitoring, united by the solution of identical strategic tasks of the state, the interconnection of its structural elements, the identity of priority contaminants and products of their transformation.&#x0D; The scientific and methodological apparatus of complex geoecological monitoring of territories under the influence of objects of aviation and space activities is presented, including predictive models of the spread and transformation of priority contaminants in environmenta
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Book chapters on the topic "Decision Based Algorithm"

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Rebitschek, Felix G. "Boosting Consumers: Algorithm-Supported Decision-Making under Uncertainty to (Learn to) Navigate Algorithm-Based Decision Environments." In Knowledge and Digital Technology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-39101-9_4.

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AbstractFinding information that is quality assured, objectively required, and subjectively needed is essential for consumers navigating uncertain and complex decision environments (e.g., retail or news platforms) and making informed decisions. This task is particularly challenging when algorithms shape environments and choice sets in the providers’ interest. On the other side, algorithms can support consumers’ decision-making under uncertainty when they are transparent and educate their users (boosting). Exemplary, fast-and-frugal decision trees as interpretable models can provide robust clas
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Jian-hui, Liu, and Han Chang-jun. "A RSSI-Based Localization Algorithm in Smart Space." In Intelligent Decision Technologies. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22194-1_66.

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Winkler, Franz. "A geometrical decision algorithm based on the gröbner bases algorithm." In Symbolic and Algebraic Computation. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/3-540-51084-2_34.

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Zuo, Yi, Masaaki Harada, Takao Mizuno, and Eisuke Kita. "Bayesian Network Based Prediction Algorithm of Stock Price Return." In Intelligent Decision Technologies. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29977-3_40.

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Kalashnykova, Nataliya I., Vyacheslav V. Kalashnikov, and Roberto C. Herrera Maldonado. "Bilevel Toll Optimization Problems: A Heuristic Algorithm Based Upon Sensitivity Analysis." In Intelligent Decision Technologies. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29977-3_14.

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Li, Jianming, Renping Lv, Xiangpei Hu, and Zhongqiang Jiang. "A GPU-Based Parallel Algorithm for Large Scale Linear Programming Problem." In Intelligent Decision Technologies. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22194-1_4.

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Li, Ren-dong. "Stock Analysis Based on Decision Tree-Based ID3 Algorithm." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40618-8_29.

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Eser, Engin, Bahar Kuloğlu, and Engin Özkan. "An Encoding–Decoding Algorithm Based on Narayana Numbers." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82342-8_7.

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Denat, Tom, and Meltem Öztürk. "Dominance Based Monte Carlo Algorithm for Preference Elicitation in the Multi-criteria Sorting Problem: Some Performance Tests." In Algorithmic Decision Theory. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67504-6_4.

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Czarnowski, Ireneusz, and Piotr Jędrzejowicz. "Kernel-Based Fuzzy C-Means Clustering Algorithm for RBF Network Initialization." In Intelligent Decision Technologies 2016. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39630-9_28.

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Conference papers on the topic "Decision Based Algorithm"

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Huang, Bosong, and Haoyi Ma. "Production Decision Optimization Based on Markov Decision Process (MDP) and Genetic Algorithm." In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE). IEEE, 2025. https://doi.org/10.1109/eespe63401.2025.10986944.

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Wu, Wenyuan, Jiaxin Lin, Bo Hu, Qiang Qin, and Hanye Huang. "Intelligent Decision Support Algorithm Based on Multimodal Data." In 2024 International Conference on Electronics and Devices, Computational Science (ICEDCS). IEEE, 2024. https://doi.org/10.1109/icedcs64328.2024.00201.

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Liu, Yi, Rongming ao, Yijing Zhang, and Jiachen Liu. "Intelligent topology decision optimization method based on knowledge map enhancement algorithm." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039750.

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Kalcheva, Neli, Maya Todorova, and Ginka Marinova. "NAIVE BAYES CLASSIFIER, DECISION TREE AND ADABOOST ENSEMBLE ALGORITHM – ADVANTAGES AND DISADVANTAGES." In 6th International Scientific Conference ERAZ - Knowledge Based Sustainable Development. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/eraz.2020.153.

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The purpose of the publication is to analyse popular classification algorithms in machine learning. The following classifiers were studied: Naive Bayes Classifier, Decision Tree and AdaBoost Ensemble Algorithm. Their advantages and disadvantages are discussed. Research shows that there is no comprehensive universal method or algorithm for classification in machine learning. Each method or algorithm works well depending on the specifics of the task and the data used.
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Yk, Shi, Jian Wu, Shiwei Wang, et al. "Research on Artificial Potential Field based Soft Actor-Critic Algorithm for Roundabout Driving Decision." In WCX SAE World Congress Experience. SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2871.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Roundabouts are one of the most complex traffic environments in urban roads, and a key challenge for intelligent driving decision-making. Deep reinforcement learning, as an emerging solution for intelligent driving decisions, has the advantage of avoiding complex algorithm design and sustainable iteration. For the decision difficulty in roundabout scenarios, this paper proposes an artificial potential field based Soft Actor-Critic (APF-SAC) algorithm. Firstly, based on the Carla simulator and Gym framework, a reinforceme
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Wei-Lun, Lin. "Decision Tree Based Decision Optimization Algorithm for Yangqin Performance." In 2022 5th International Conference on Mechatronics, Robotics and Automation (ICMRA). IEEE, 2022. http://dx.doi.org/10.1109/icmra56206.2022.10145665.

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Ma, Ning, and Jianhe Guan. "Research on AHP decision algorithms based on BP algorithm." In 2ND INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, RESOURCE AND ENVIRONMENTAL ENGINEERING (MSREE 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5005288.

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Chen, Wangjie, Wenlong Li, Weiqiang Zhu, Songhua Shi, Mingyu Zhou, and Zhenhong Fan. "Group Intelligent Decision Optimization Based on Fireworks Algorithm." In SAE 2024 Intelligent and Connected Vehicles Symposium. SAE International, 2024. https://doi.org/10.4271/2024-01-7047.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This study delves into the application of the fireworks algorithm (FWA) based on swarm intelligence decision in multi-device resource scheduling. By simulating the process of fireworks explosion, this algorithm efficiently searches for global optimal solutions, demonstrating good stability and optimization performance. In comparison to traditional heuristic algorithms, FWA shows advantages such as simplicity, local coverage, and robustness when addressing multi-device resource scheduling issues. Through experimental vali
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Xudong, Song, and Cheng Xiaolan. "Decision Tree Algorithm based on Sampling." In 2007 IFIP International Conference on Network and Parallel Computing Workshops (NPC 2007). IEEE, 2007. http://dx.doi.org/10.1109/npc.2007.133.

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Xudong, Song, and Cheng Xiaolan. "Decision Tree Algorithm based on Sampling." In 2007 IFIP International Conference on Network and Parallel Computing Workshops (NPC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icnpcw.2007.4351564.

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Reports on the topic "Decision Based Algorithm"

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Kim, Dai H. A Highly Functional Decision Paradigm Based on Nonlinear Adaptive Genetic Algorithm. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada281457.

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Kostrzewski, Andrew, and Jeongdal Kim. A Highly Functional Decision Paradigm Based on Nonlinear Adaptive Genetic Algorithm. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada344278.

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O'Neill, Francis, Kristofer Lasko, and Elena Sava. Snow-covered region improvements to a support vector machine-based semi-automated land cover mapping decision support tool. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45842.

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This work builds on the original semi-automated land cover mapping algorithm and quantifies improvements to class accuracy, analyzes the results, and conducts a more in-depth accuracy assessment in conjunction with test sites and the National Land Cover Database (NLCD). This algorithm uses support vector machines trained on data collected across the continental United States to generate a pre-trained model for inclusion into a decision support tool within ArcGIS Pro. Version 2 includes an additional snow cover class and accounts for snow cover effects within the other land cover classes. Overa
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Tipton, Kelley, Brian F. Leas, Emilia Flores, et al. Impact of Healthcare Algorithms on Racial and Ethnic Disparities in Health and Healthcare. Agency for Healthcare Research and Quality (AHRQ), 2023. http://dx.doi.org/10.23970/ahrqepccer268.

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Objectives. To examine the evidence on whether and how healthcare algorithms (including algorithm-informed decision tools) exacerbate, perpetuate, or reduce racial and ethnic disparities in access to healthcare, quality of care, and health outcomes, and examine strategies that mitigate racial and ethnic bias in the development and use of algorithms. Data sources. We searched published and grey literature for relevant studies published between January 2011 and February 2023. Based on expert guidance, we determined that earlier articles are unlikely to reflect current algorithms. We also hand-se
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Alwan, Iktimal, Dennis D. Spencer, and Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.

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Objective: To compare the performance of popular machine learning algorithms (ML) in mapping the sensorimotor cortex (SM) and identifying the anterior lip of the central sulcus (CS). Methods: We evaluated support vector machines (SVMs), random forest (RF), decision trees (DT), single layer perceptron (SLP), and multilayer perceptron (MLP) against standard logistic regression (LR) to identify the SM cortex employing validated features from six-minute of NREM sleep icEEG data and applying standard common hyperparameters and 10-fold cross-validation. Each algorithm was tested using vetted feature
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Paule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER, and Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.

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In the context of climate change and the environmental and energy constraints we face, it is essential to develop methods to encourage the implementation of efficient solutions for building renovation. One of the objectives of the European PRELUDE project [1] is to develop a "Building Renovation Roadmap"(BRR) aimed at facilitating decision-making to foster the most efficient refurbishment actions, the implementation of innovative solutions and the promotion of renewable energy sources in the renovation process of existing buildings. In this context, Estia is working on the development of infer
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Borkman, Steve, Marlo Verdesca, and Jon Watkins. Algorithms for Ground Soldier Based Simulations and Decision Support Applications. Phase 1. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada560713.

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Seginer, Ido, James Jones, Per-Olof Gutman, and Eduardo Vallejos. Optimal Environmental Control for Indeterminate Greenhouse Crops. United States Department of Agriculture, 1997. http://dx.doi.org/10.32747/1997.7613034.bard.

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Increased world competition, as well as increased concern for the environment, drive all manufacturing systems, including greenhouses, towards high-precision operation. Optimal control is an important tool to achieve this goal, since it finds the best compromise between conflicting demands, such as higher profits and environmental concerns. The report, which is a collection of papers, each with its own abstract, outlines an approach for optimal, model-based control of the greenhouse environment. A reliable crop model is essential for this approach and a significant portion of the effort went i
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Pasupuleti, Murali Krishna. Optimal Control and Reinforcement Learning: Theory, Algorithms, and Robotics Applications. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv225.

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Abstract: Optimal control and reinforcement learning (RL) are foundational techniques for intelligent decision-making in robotics, automation, and AI-driven control systems. This research explores the theoretical principles, computational algorithms, and real-world applications of optimal control and reinforcement learning, emphasizing their convergence for scalable and adaptive robotic automation. Key topics include dynamic programming, Hamilton-Jacobi-Bellman (HJB) equations, policy optimization, model-based RL, actor-critic methods, and deep RL architectures. The study also examines traject
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Sonmez Turan, Meltem. Ascon-Based Lightweight Cryptography Standards for Constrained Devices. National Institute of Standards and Technology, 2025. https://doi.org/10.6028/nist.sp.800-232.

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In 2023, the National Institute of Standards and Technology (NIST) announced the selection of the Ascon family of algorithms designed by Dobraunig, Eichlseder, Mendel, and Schläffer to provide efficient cryptographic solutions for resource-constrained devices. This decision emerged from a rigorous, multi-round lightweight cryptography standardization process. The Ascon family includes a suite of cryptographic primitives that provide Authenticated Encryption with Associated Data (AEAD), hash function, and eXtendable Output Function (XOF) capabilities. The Ascon family is characterized by lightw
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