Search Results - intelligence ai ((cell algorithm) OR (((learning algorithm) OR (cloud algorithm))))

Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…EMS strategies; AI-based algorithms categories, functions and hybridization; the state-of-art and future direction of AI-based algorithms and HFCEVs? …”

A Survey on Information-Centric Networking with Cloud Internet of Things and Artificial Intelligence by Farhan Ahmed Karim, Azana Hafizah Mohd Aman, Rosilah Hassan, Kashif Nisar

“…We initially rate the configuration of ICN with cloud or edge IoT and AI (ICN-CIoT-AI) in this study so that readers may learn about the latest trends and merging of ICN-CIoT-AI. …”
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Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases by Kartinah, Zen, Saju, Mohanan, Seleviawati, Tarmizi, Noralifah, Annuar

“…Latency in real-time processing is influenced by many factors such as artificial intelligence (AI) computing algorithm, device processing capabilities, the frameworks, and also the distance from the cloud infrastructure. …”
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A Modular Intelligent Control Framework for Scalable Biohydrogen Production in Microbial Electrolysis Cells by Mohd Farid, Atan, Mohamad Afiq, Mohd Asrul, Andrica Claudia, Henry, Hafizah, Abdul Halim Yun, Ivy Tan, Ai Wei, Josephine Lai, Chang Hui

“…This review traces the evolution of five control paradigms, including voltage/proportional-integral-derivative (PID), model-based, adaptive, fuzzy logic, and artificial-intelligence (AI) systems, as well as hybrid intelligent controllers, and benchmarks each against scalability, dynamic responsiveness, and energy-recovery performance. …”
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Implementing server-side federated learning in an edge-cloud framework for precision aquaculture by Ng, Bryan Jing Hong

“…In this project, research and literature reviews were conducted to explore the current technologies in smart aquaculture, federated learning, and data privacy. Reviews include systems using IoT and AI-based models, along with analysis of different federated learning algorithms such as FedSGD, FedAvg, and FedProx, and privacypreserving methods such as DA, SA, HE and CKKS encryption. …”
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A bibliometric analysis: AI-driven data placement optimization in cloud replication environments by Mohd Ali, Fazlina, Mat Daud, Marizuana, Bahar, Nurhidayah, Mohd Salleh, Syahanim, Nor Rashid, Fadilla ‘Atyka, Md Yunus, Nur Arzilawati

“…Data placement strategy using artificial intelligence (AI) in cloud replication environments has garnered significant attention in recent years. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…Since the emergence of AIS, it has proved itself as an area of computational intelligence. …”
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Comparative analysis of danger theory variants in measuring risk level for text spam messages by Zainal K., Jali M.Z., Hasan A.B.

Hybrid of convolutional neural network algorithm and autoregressive integrated moving average model for skin cancer classification among Malaysian by Chin, Chee Ka, Dayang Azra, Awang Mat, Abdulrazak Yahya, Saleh

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Characteristics of machining data and machine learning models - A case study by Natarajan, Elango, Fiorna, Vxynette, Al-Talib, Ammar Abdulaziz Majeed, Elango, Sangeetha, Gnanamuthu, Ezra Morris Abraham, Sarah Atifah, Saruchi

“…One of the key technologies or preferable methods to increase the productivity is implementing prediction models or machine learning (ML) algorithms in production. This article is aimed to show a comprehensive review on AI implementation in machining of materials, and to present methodology in prediction model development. …”
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin by Samsudin, Fahmi

“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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Artificial Intelligence in accounting / Akma Hidayu Dol @ Abdul Wahid and Rafizan Abdul Razak by Dol @ Abdul Wahid, Akma Hidayu, Abdul Razak, Rafizan

“…Furthermore, AI algorithms can reconcile transactions and identify discrepancies. …”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…The advancement of Artificial Intelligence (AI) has introduced complex methods such as deep learning that would automate the classification of blood cells in a fast and accurate manner Thus, the study of White Blood Cells (WBCs) classification using deep learning techniques is proposed in this research. …”
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Real-time personal protective equipment compliance detection using you only look once by Nurhanisah, Aminuddin, Nor Azuana, Ramli, Pratondo, Agus

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An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction by JUNE, KHOO YAN

“…In this study, an intelligent hybrid model using CNN and RNN for crop yield prediction is proposed. …”
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Future trends in auditing: preparing for a technology-driven landscape by Muhammad Arnim, Nur Afiqah Najwa, Abd Razak, Siti Noor Azmawaty

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Self-driving car with Artificial Intelligence (AI) technology / Asrul Amin Mohd Isa ... [et al.] by Mohd Isa, Asrul Amin, Hasnan, Aimuni Aina, Hashim, Zuyyin, Othman, Jamal

“…The self-driving car is a type of autonomous vehicle that can drive autonomously based on Artificial Intelligence (AI). It is based on the use of sensors, actuators, sophisticated algorithms, machine learning systems, and robust processors. …”
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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

“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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