Search Results - (( intelligence based dea algorithm ) OR ( intelligence _ ((data algorithm) OR (acs algorithm)) ))

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.

“…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. …”
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Attitude Control System for InnoSAT by Anon

“…To develop attitude control algorithms software; ACS is the part of the ADCS payload. …”
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Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

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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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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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Analysis of Delay Performance on the Intelligent Fuzzy Logic Dynamic Bandwidth Allocation Algorithm by Radzi N.A.M., Din N.M., Al-Mansoori M.H., Mustafa I.S., Majid M.S.A.

“…In this paper, we study the delay performance of an intelligent fuzzy logic based dynamic bandwidth allocation (IFLDBA) algorithm for EPON. …”

Development of hybrid artificial intelligent based handover decision algorithm by Aibinu, Abiodun Musa, Onumanyi, Adeiza J., Adedigba, A. P., Ipinyomi, M., Folorunso, T. A., Salami, Momoh Jimoh Eyiomika

“…Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. …”
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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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Intelligent decision support systems for oil price forecasting by Chiroma, Haruna, Zavareh, Adeleh Asemi, Baba, Mohd Sapiyan, Ibrahim, Adamu Abubakar, Gital, Abdulsam Ya'u, Zambuk, Fatima Umar

“…This research studies the application of hybrid algorithms for predicting the prices of crude oil. Brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. …”
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Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study by Abu-Samah A., Abdul Razak N.N., Mohamad Suhaimi F., Jamaludin U.K., Chase G.

Document clustering using hybrid lda- kmeans by Foong, O.-M., Ismail, A.N.

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Document clustering using hybrid lda- kmeans by Foong, O.-M., Ismail, A.N.

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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking by Suman, S., Hussi, F.A., Nicolas, W., Malik, A.S.

“…Therefore, it would be extremely advantageous to develop an intelligent algorithm to inspect the WCE images. This research aims to develop an algorithm to enhance wireless capsule endoscopy images and analyses them to detect Ulcer located in small intestine. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking by Suman, S., Hussi, F.A., Nicolas, W., Malik, A.S.

“…Therefore, it would be extremely advantageous to develop an intelligent algorithm to inspect the WCE images. This research aims to develop an algorithm to enhance wireless capsule endoscopy images and analyses them to detect Ulcer located in small intestine. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…The algorithms are ACS(GA), ACS+GA, ACS(TS), and ACS+TS. …”
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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.

“…The statistical evidence indicated that the DL algorithms performed well in the prediction of heart failure with AUC of 0.843 and CI 0.840-0.845, while in the ML algorithm, the gradient boosting machine (GBM) achieved an average accuracy of 91.10% in predicting heart failure. …”
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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.

“…The statistical evidence indicated that the DL algorithms performed well in the prediction of heart failure with AUC of 0.843 and CI 0.840-0.845, while in the ML algorithm, the gradient boosting machine (GBM) achieved an average accuracy of 91.10% in predicting heart failure. …”
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Stress Classification using Deep Learning with 1D Convolutional Neural Networks by Abdulrazak Yahya, Saleh, Khai Xian, Lau

“…Identifying whether someone is suffering from stress is crucial before it becomes a severe illness. Artificial Intelligence (AI) interprets external data, learns from such data, and uses the learning to achieve specific goals and tasks. …”
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An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Saeed, Faisal

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