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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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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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Backpropagation algorithm for rice yield prediction by Puteh, Saad, Mohamed Rizon, Mohamed Juhari, Nor Khairah, Jamaludin, Siti Sakira, Kamarudin, Aryati, Bakri, Nursalasawati, Rusli

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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani by Jailani, Muhammad Irfan Zahin

“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…Upon the completion of data collection and data pre processing, the eABC-LSSVM algorithm is designed and developed. The predictability of eABC-LSSVM is measured based on five statistical metrics which include Mean Absolute Percentage Error (MAPE), prediction accuracy, symmetric MAPE (sMAPE), Root Mean Square Percentage Error (RMSPE) and Theils’ U. …”
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Prediction of blood-brain barrier permeability of compounds by machine learning algorithms by Feng, Tan wei, Raihana Zahirah, Edros, Ngahzaifa, Ab Ghani, Siti Umairah, Mokhtar, Dong, Ruihai

“…In this work, using the KNIME Analytics platform, 4 predictive models were developed with 4 ML algorithms followed by a ten-fold cross-validation approach to predict the external validation set. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…With this project creates a mobile app that analyse the mood pattern which also correspond with menstrual cycle to be able to predict mood. The development model used for this project is Agile model development cycle. …”
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Investigating the application of artificial intelligence for earthquake prediction in Terengganu by Marhain S., Ahmed A.N., Murti M.A., Kumar P., El-Shafie A.

Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

“…Referring to the experimental results, as opposed to the GP and ANN methods, the ELM approach enhanced generalization ability and predictive accuracy. Moreover, achieved results indicated that the developed ELM models can be used with confidence for further work on formulating novel model predictive strategy in shear strength and ductility of steel concrete composite. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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A framework for the development of an optimized artificial intelligence model for diabetes mellitus prediction and treatment recommendation by Islam, Md Ziarul, Hassan, Mohd Khairul Azmi, Amir Hussin, Amir 'Aatieff

“…This study presents a framework that leverages the Indian Pima Diabetes dataset to develop and evaluate an optimized artificial intelligence (AI) model for diabetes prediction and treatment guidance. …”
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. …”
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An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

“…This paper presents work on developing a software system for predicting crop yield from climate and plantation data. …”
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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. …”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique by ‘Ainaa Nur Batrisyia binti Abdul Rahman, -

“…Apart from that, DC-DC boost converter would be the intermediate in developing the algorithm to the system. The extraction of the maximum output power can be achieved through this mechanism. …”
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Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone by Md Jamal, Norezmi

“…Moreover, the task of removing noises without causing speech distortion is also challenging, in which the quality and intelligibility of speech are affected. In order to overcome these issues, a supervised Deep Neural Network (DNN) algorithm predicted constrained Wiener Filter (cWF) target mask algorithm based on extracted Gammatone filter bank power spectrum (GF-TF) features and trained model is developed. …”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin by Che Wan Samsudin, Che Wan Sufia

“…The development of a predictive model for condominium prices using the Particle Swarm Optimization-Random Forest approach is the key focus of this research project. …”
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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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