Search Results - (( intelligence system tree algorithm ) OR ( intelligence a ((svm algorithm) OR (_ algorithm)) ))

Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

“…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”

Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…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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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. …”
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A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems by Hayder G., Solihin M.I., Kushiar K.F.B.

Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

“…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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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…This research paper focuses on the development of a cardiovascular disease prediction system particularly a heart disease, by developing machine learning classifiers, for instance, Support Vector Machine (SVM), Decision Tree, and XGBoost Classifiers. …”
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Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

“…This research paper focuses on the development of a cardiovascular disease prediction system particularly a heart disease, by developing machine learning classifiers, for instance, Support Vector Machine (SVM), Decision Tree, and XGBoost Classifiers. …”
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Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

“…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

“…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 intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

“…Preventing DoS at the network or infrastructure level typically depends on implementing an IDS. This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…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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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

“…A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System by Abad, Azad

“…This study has explored an intelligent video surveillance system, presented by real time moving detection, object classification and interpreting the activity of the people by employing image segmentation and new approach in artificial intelligence called artificial immune system. …”
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A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

The fuzzy decision tree application to a power system problem by Lo K.L., Abidin H.I.H.Z

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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…This study contributes to the field by proposing a new regularization technique, demonstrating the effectiveness of the Algorithm Adaptation framework, and providing insights into the associations between diabetes complications. …”
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

“…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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