Search Results - (( simultaneously interactive learning algorithm ) OR ( java implementation phase algorithm ))

An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…All the algorithm for the engine has been developed by using Java script language. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

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Ethical Considerations in the Use of AI in Learning and Teaching for Special Education. by Noor Aida, Md Noor, Siti Noor Aneeis, Hashim, Juereanor, Mat Jusoh, Leha, Saliman, Shazali, Johari, NorHamidah, Ibrahim, Zaim Azizi, Abu Bakar, Mohd Norazmi, Nordin

“…The rapid integration of Artificial Intelligence (AI) within the domain of Special Education (SPED) has catalyzed a paradigm shift in how students with diverse learning needs access curriculum and interact with their environment. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies by Ahmad Isiyaka, H., Jumbri, K., Soraya Sambudi, N., Uba Zango, Z., Ain Fathihah Binti Abdullah, N., Saad, B.

“…The ANN learning algorithm performed significantly in predicting and validating the experimental conditions designed by the RSM model. …”
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies by Ahmad Isiyaka, H., Jumbri, K., Soraya Sambudi, N., Uba Zango, Z., Ain Fathihah Binti Abdullah, N., Saad, B.

“…The ANN learning algorithm performed significantly in predicting and validating the experimental conditions designed by the RSM model. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…Existing works and solutions focused on separate models for recognizing the residents, activities and interactions. On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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