Search Results - (( intelligence systematic learning algorithm ) OR ( intelligence based data 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…”

Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…Combining AI and blockchain technology can handled some of the drawbacks of these two technical ecosystems effectively. AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

“…Combining AI and blockchain technology can handled some of the drawbacks of these two technical ecosystems effectively. AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review by Hashim, Suraya, Omar, Muhd Khaizer, Ab. Jalil, Habibah, Mohd Sharef, Nurfadhlina

“…To gain a better understanding of the concept and implementation of a personalized learning environment employing AI technology, a systematic literature review (SLR) was conducted to identify the trends of technologies and Artificial Intelligence in Education (AIEd) in promoting personalized learning. …”
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Systematic review of intrusion detection system based on machine learning techniques for internet of things by Idris, Muhammad, Md Yasin, Sharifah, Audi, Giade Hamza

“…Machine learning (ML)-based intrusion detection systems (IDS) offer a promising approach to enhancing IoT security by analysing real-time data from IoT devices. …”
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A systematic and critical review on effective utilization of artificial intelligence for bio-diesel production techniques by Ahmad, Junaid, Awais, Muhammad, Rashid, Umer, Ngamcharussrivichai, Chawalit, Raza Naqvi, Salman, Ali, Imtiaz

“…The AI-enabled biodiesel prediction methods consist of several stages, i.e., biodiesel data collection, biodiesel data preprocessing, developing, and tuning machine learning (ML) algorithm on biodiesel data, and predicting unknown biodiesel properties. …”
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Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024) by Ibrahim Brian, Muhammad Shyazzwan

“…This Systematic Literature Review (SLR) examines the integration of Artificial Intelligence (AI) in English Language Learning (ELL) with the aim of reimagining classrooms as creative, inclusive, and technology-enhanced spaces. …”
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A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges, weaknesses and recommendation... by Hakim M., Omran A.A.B., Ahmed A.N., Al-Waily M., Abdellatif A.

“…Deep Learning is now an extraordinarily popular research topic in the field and a promising approach for detecting intelligent bearing faults. This paper aims to give a comprehensive overview of Deep Learning (DL) based on bearing fault diagnosis. …”

A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients by Rahman, Md Saidur, Md Nor, Nor Saadah

“…Fourteen studies published from 2018 to 2024 were reviewed in the systematic review to learn how AI technology was incorporated to improve care for CKD patients. …”
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Artificial intelligence-driven anticancer peptide discovery by Wu, Junrui, Ji, Shuaiqi, Sahibzada, Kashif Iqbal, Lou, Mengxue, An, Feiyu, Li, Wenqian, Guo, Jiawei, Zhang, Taowei, Zhang, Xinyi, Chou, Yilin, Zhang, Henan, Jin, Hao, Ma, Teng, Liu, Weichi, Alikulov, Begali, Golovneva, Natalia Alekseevna, Foo, Hooi Ling, Kuralay, Issayeva, Sun, Zhihong, Wei, Dongqing, Wu, Rina

“…Artificial intelligence (AI) has provided new methods to address these challenges, significantly improving the efficiency and accuracy of ACP screening through the application of machine learning and deep learning algorithms. …”
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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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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…The increasing volumes of electronic healthcare records (EHR) encourage the development of the application and research of machine learning (ML) in digital health. Promoting ML in healthcare based on EHR can enhance health management for increased intelligence, safety, and efficiency. …”
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Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML) by Kabbashi, Nassereldeen Ahmed, Hasan, Tahsin Fuad, Alam, Md Zahangir, Saleh, Tanveer, Hassan Abdalla Hashim, Aisha

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Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

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Application of phi (Φ), the golden ratio, in computing: a systematic review by Akhtaruzzaman, M, Tanvin, Jamal Uddin, Shafie, Amir Akramin, Shahryer, Fahim, Halder, Sachitra

“…The review also categorizes findings by their specific applications and contexts, providing valuable insights into φ’s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.