Search Results - (( intelligence based modeling algorithm ) OR ( intelligence about learning algorithm ))

Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning by Taotao, Xu, Musdi, Shanat, Brendan Chan, Kah Le, Wei, Zhang

“…Based on the design of modeling elements of Luoshan shadow puppets, this paper analyzes the characteristics of visual elements of shadow puppet creative goods, puts forward an intelligent design algorithm of shadow puppet creative goods based on DL, and explores the computer-aided shadow puppets modeling design strategy driven by artificial intelligence. …”
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Auto raise hand in Microsoft teams (API/Extension) by Teh, Boon Hin

“…Artificial Intelligence focuses on developing intelligences of machines, by developing algorithms, machines are able to learn from data and patterns, even perform tasks that require human intelligence, such as visual perception, speech recognition, and decision-making. …”
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Ethical concerns about the applications of artificial intelligence in healthcare practices: an explanatory review by Hassan, Ismail Bile, Hashi, Abdurezak Abdulahi

“…Though the use of artificial intelligence and machine-learning algorithms is rapidly growing in various healthcare practices with promising potentials, however the use of computer-generated applications in healthcare sector have raised certain ethical concerns about the safety and reliability of these applications. …”
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Overhead view based person counting using deep learning by Kaw, Chee Zhao

“…However, the counting accuracy of Centroid Tracking algorithm is about 22.2% lower than the DeepSORT tracking algorithm. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Ontology based approach to Fuzzy student model design by Muhammad Sani, Salisu, Mohd Aris, Teh Noranis

“…An important component of these elearning systems in use today is called the intelligent tutoring system (ITS). ITS is a software system designed using artificial intelligent techniques (comprising of Fuzzy Logic, Neural-Networks, Bayesian networks, Ontology, Genetic Algorithms and Software Agents) to provide a personalized tutoring adaptable to each student based on his/her profile or characteristics. …”
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A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Alam, Mohammad Nur‑E, Soudagar, Manzoore Elahi Mohammad

“…This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). …”
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A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Nur‑E‑Alam, Mohammad, Soudagar, Manzoore Elahi Mohammad

“…This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

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Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

“…In the agent-based approach to middleware, the agent’s property such as autonomous, mobile and intelligent are suitable as e-assistance tool for big data management. …”
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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 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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Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

“…The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model using different initial conditions based on real data. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…Through rank selection technique, the chromosomes are sorted based on the fitness function to learn about the population of current generation. …”
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Agent architectures (building chatterbot) / Umi Aimah Abu Bakar by Umi Aimah , Abu Bakar

“…While MILAH, it has no neural network, no complex knowledge presentation, no fuzzy logic, no genetic algorithm and no major parsing. MILAH uses Case Based Reasoning (CBR). …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…The designed multilayer decision-based fuzzy logic model effectively solves the path planning queries in crowded and complex situations without any failure. …”
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Fault diagnosis in unbalanced radial distribution networks using generalised regression neural network by Mirzaei, Maryam

“…The results were compared with radial basic function neural network (RBFN) and feed forward neural network (FFNN). The artificial intelligence (AI)-based fault locator has been implemented on a typical IEEE 13 node test feeder as short feeder with the feeder’s nominal voltage is 4.16 kV. …”
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