Search Results - (( intelligence based data algorithm ) OR ( intelligence model (drops OR drop) algorithm ))

Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

“…Complex networks; Drops; Forecasting; Iterative methods; Network architecture; Network layers; Optimization; Rivers; Stochastic models; Stochastic systems; Stream flow; Time series; Engineering applications; Gradient-decent algorithm; Intelligent Water Drops (IWD); Multi layer perceptron; Multi-layer perceptron neural networks; Optimization algorithms; Streamflow forecasting; Time series prediction; Multilayer neural networks…”

Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

“…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence by Singh, D.N., Murugamani, C., Kshirsagar, P.R., Tirth, V., Islam, S., Qaiyum, S., Suneela, B., Al Duhayyim, M., Waji, Y.A.

“…Goal of this approach is to treat the wastewater treatment model with industrial data. Algorithms of the artificial neural network (ANN) were employed progressively to predict parameters for wastewater plants. …”
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

“…However, these methods are less effective when the non-linearity, complexity, and modeling uncertainties of the system increase. In recent years, a new discipline, known as artificial intelligence-based methods, has emerged, which allows the behavior of the system to be studied using operational data. …”
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Inverse modeling of mass transferprocess in the RDC column by fuzzy approach by Maan, Normah, Talib, J., Arshad, K. A., Ahmad, T.

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An analysis of scheduling scheme for QoS guaranteed interactive multimedia over high speed wireless campus networks by Alam, M.K., Abd Latif, Suhaimi, Masud, Mosharrof Hussain, Akter, Mahmuda

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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

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AI-enhanced generative design for efficient heat exchangers in thermoelectric generators: revolutionizing waste heat recovery in thermoelectricity / Andrew Robert Martin Hughes ...... by Andrew, Robert Martin Hughes, Bhathal Singh, Baljit Singh, Remeli, Muhammad Fairuz, Peixer, Guilherme Fidelis, Ratan Singh, Wandeep Kaur

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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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Blood cell classification using deep learning by Liaw, Mun Kin

“…The learning rate was fine-tuned using the Tuner library from Keras to find the optimal value that generates a well-established model. As a result, the finalized model which consists of batch size of 16, learning rate of 0.0009, global pooling layer, 4 number of classes dropped to 3 number of classes and 3 dense layers achieved a testing accuracy of approximately 63% and validation accuracy of 99%.…”
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A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

“…Whereas the process of examining through the web pages, retrieving and searching the relevant data in a liTML page, and selecting the best satisfying data are based on the features and operations of the Genetic Algorithms.…”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

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Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

“…Whereas kernel-based clustering algorithm is developed for finding clusters in climate data. …”
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An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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