Search Results - intelligence ai ((cpdod algorithm) OR (svm algorithm))

Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

“…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…Statistical models are the main approaches but recently, Artificial Intelligence (AI) techniques have been popular due to their ability to account for flexible data patterns. …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

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Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

“…Hereby, we present a complex framework that involves Internet of Things (IoT) devices, Neural Networks, Artificial Intelligence (AI) to make decisions in traffic controlling, environmental issues and safety. …”
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Development of an accurate AI-based dermatology assistant for skin disease recognition using YOLOv8 models by Huzaini, Muhammad Irfan Darwish, Mansor, Hasmah, Gunawan, Teddy Surya, Ahmad, Izanoordina

“…The research compares various algorithms, such as SVM, YOLOv3, YOLOv4, and Dual-Architecture CNN, through a comprehensive review of existing AI applications in dermatology. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill by Abunama, Taher, Othman, Faridah, Ansari, Mozafar, El-Shafie, Ahmed

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Acoustic Emission and Artificial Intelligent Methods in Condition Monitoring of Rotating Machine – A Review by Yasir , Hassan Ali, Salah, M. Ali, Roslan, Abd Rahman, Raja Ishak, Raja Hamzah

“…This paper provides a review on using acoustic emission (AE) technique combined with artificial intelligence (AI) methods in the field of machinery condition monitoring and fault diagnosis. …”
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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.

GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

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A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

“…Machine Learning (ML) is an area of Artificial Intelligent (AI) with a concept that a computer program can learn and familiarize to new data without human intervention. …”
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Optimized Model Inputs Selections for Enhancing River Streamflow Forecasting Accuracy Using Different Artificial Intelligence Techniques by Tofiq Y.M., Latif S.D., Ahmed A.N., Kumar P., El-Shafie A.

Crop yield prediction in agriculture: a comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability by Jabed, Md. Abu, Azmi Murad, Masrah Azrifah

“…This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. …”
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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

“…To overcome these challenges, the current research aims to develop a SpatioTemporal Decision-Making (STDM) model based on Geospatial Artificial Intelligence (GeoAI) to locate onshore wind-solar hybrid plants. …”
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Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM by Shozib, I.A., Ahmad, A., Rahaman, M.S.A., Abdul-Rani, A.M., Alam, M.A., Beheshti, M., Taufiqurrahman, I.

“…The four AI models applied in this study were Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF) and Extra Trees (ET). …”
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Dental disease detection using Convolutional Neural Network (CNN) / Faiznur Kamallul Ariffin by Kamallul Ariffin, Faiznur

“…Convolutional Neural Networks (CNN) are a type of artificial neural network that is commonly used in the field of Artificial Intelligence (AI). Many types of algorithms can be used for detection such as Support Vector Machines (SVM), Recurrent Neural Networks (RNNs), and many more but CNN shows the best result and accuracy which is 99%.…”
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Global spatial suitability mapping of wind and solar systems using an explainable aI-based approach by Sachit, Mourtadha Sarhan, Mohd Shafri, Helmi Zulhaidi, Abdullah, Ahmad Fikri, Mohd Rafie, Azmin Shakrine, Gibril, Mohamed Barakat A.

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Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis by Baashar, Y., Alkawsi, G., Alhussian, H., Capretz, L.F., Alwadain, A., Alkahtani, A.A., Almomani, M.

“…Cardiovascular diseases (CVDs), in particular, are the main cause of death worldwide, accounting for 30 of all fatalities in the United States and 45 in Europe. Artificial intelligence (AI) approaches such as machine learning (ML) and deep learning (DL) models are playing an important role in the advancement of heart failure therapy. …”
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