Search Results - intelligence _ ((((rsa algorithm) OR (tree algorithm))) OR (means algorithm))
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…For the objective of classifying FI in terms of fraud or not, the Intelligent Information System for Financial Institutions (IISFI) relying on Supervised ML (SML) Algorithms has been created in this work. …”
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Privacy in medical emergency system: cryptographic and security aspects
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An Intelligent System Approach to the Dynamic Hybrid Robot Control
Published 1996“…This was because a robot can be seen as a physical intelligent system which interacts with the real world environment by means of its sensors and actuators. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat
Published 2016“…The simulation results show the AMS algorithm significantly improves the performance over RSA-MSDU and the standard for real-time traffic in terms of reducing average delay and packet loss up to 56% and 24% respectively. …”
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Secure Image Steganography Using Encryption Algorithm
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). The result revealed that the ANN performance had the highest accuracy when training using the LM training algorithm. …”
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Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study
Published 2023“…Decision support systems; Forecasting; Intensive care units; Medical informatics; Trees (mathematics); Accurate prediction; Causal Bayesian network; Discretization algorithms; Discretizations; Glycemic control; Intelligent mechanisms; Performance prediction; Variable selection; Bayesian networks…”
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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach
Published 2024Subjects:Conference Paper -
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The algorithm involved the construction of the nodes of a lexicographic tree that represent frequent patterns. …”
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12
An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Published 2022“…This is grounded in the fact that Bagged Trees is most effective algorithm for the said application and Medium Trees is the most efficient one. …”
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A proposed model for text and image encryption using different techniques
Published 2023“…In this paper, the Rivest Shamir Adleman 3 key (RSA3k) algorithm is used but in a new technique to encrypt and decrypt text. …”
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction
Published 2023“…Thus, it is highly required to examine the performance of various artificial intelligence techniques including standalone and hybrid algorithms for accurate ozone concentration prediction at the tropospheric layer. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate
Published 2025“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea
Published 2018“…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
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Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia
Published 2023“…artificial intelligence; artificial neural network; numerical model; prediction; regression analysis; solar power; solar radiation; Malaysia; algorithm; artificial intelligence; decision tree; Malaysia; solar energy; Algorithms; Artificial Intelligence; Decision Trees; Malaysia; Neural Networks, Computer; Solar Energy…”
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm
Published 2014“…Moreover, cache pollution is a drawback of traditional web caching policies such as Least Frequently Used (LFU), Least Recently Used (LRU), and Greedy Dual Size (GDS) where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
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