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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…This algorithms were selected based on previous literature review in price prediction. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning by Usman F., Nanda, Sumantyo J.T.S.

“…Earthquakes can inflict significant damage to structures and infrastructures. This paper presents a machine learning model to predict ground surface deformation (GDS) induced by earthquake events. …”

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model by Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca

“…In this study, we used an optimized machine learning technique based on Particle Swarm Optimization-Support Vector Regression (PSO-SVR) to learn the relationship between its structural properties with its lattice constants. …”
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

“…Hydrogeneration prediction typically has composite structures such as nonlinearity, non-stationarity, and fluctuation, which converts its predicting to be very tough. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Integration of GWO-LSSVM for time series predictive analysis by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Bariah, Yusob, Ernawan, Ferda

“…In most cases, disaster prevention operation such flood warning scheme proved to be more efficient in mitigating the effects of major floods than structural measures. Thus, for this study, a hybrid algorithm of LSSVM with one of the recent bio-inspired optimization algorithm, namely Grey Wolf Optimizer (GWO-LSSVM) is presented for water level prediction. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”

Feature selection and prediction of heart disease using machine learning approaches by Molla, M. M.Imran, Islam, Md Sakirul, Shafi, A. S.M., Alam, Mohammad Khurshed, Islam, Md Tarequl, Jui, Julakha Jahan

“…In the proposed research, by using the cardiovascular disease dataset, we created a machine-learning model to predict cardiac disease. In this paper, it is capable of recognizing and classifying the heart disease patient from healthy people by using three standard machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). …”
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A modified weight optimisation for higher-order neural network in time series prediction by Husaini, Noor Aida

“…The performance of MCS-MCMC learning algorithm was validated with several test functions and compared with those of MCS learning algorithm. …”
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A Pioneering Approach to Predicting the Shear Strength of RC Beams by Employing Artificial Intelligence Techniques by Hakim, S. J. S., Mhaya, A. M., Ibrahim, M. H. W., Mohammadhasani, M., Mokhatar, S. N., Paknahad, M., Kamarudin, A. F.

“…The outcomes demonstrated that both methods exhibited favourable predictive capabilities. Nevertheless, the ANFIS architecture proposed, which incorporates a hybrid learning algorithm, outperformed the multilayer feedforward ANN that utilizes the backpropagation algorithm. …”
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A Pioneering Approach to Predicting the Shear Strength of RC Beams by Employing Artificial Intelligence Techniques by Hakim, S. J. S., Mhaya, A. M., Ibrahim, M. H. W., Mohammadhasani, M., Mokhatar, S. N., Paknahad, M., Kamarudin, A. F.

“…The outcomes demonstrated that both methods exhibited favourable predictive capabilities. Nevertheless, the ANFIS architecture proposed, which incorporates a hybrid learning algorithm, outperformed the multilayer feedforward ANN that utilizes the backpropagation algorithm. …”
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