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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…To our knowledge, there is still no implementation of machine learning models on green building valuation features for building price prediction compared to conventional building development. …”
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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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Hardware Design Of Random Number Generator And Random Walk-Onboundary Algorithm To Compute Unit Cube Capacitance In Fpga by Niun, Cheah How

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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Statistical analysis, ciphertext only attack, improvement of generic quasigroup string transformation and dynamic string transformation by Hassan Disina, Abdulkadir, Jamel, Sapiee, Abubakar Pindar, Zahraddeen, Mat Deris, Mustafa

“…Quasigroup String transformation is one of those primitives that have many applications in cryptographic algorithms, Hash functions, and Pseudo-Random Number Generators. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

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The Random forest algorithm for modelling the overspending behaviour of Malaysian households income class by Liyana Ihkwani Abdul Latif, Azuraliza Abu Bakar, Zulaiha Ali Othman, Mohd Suhaidi Abdul Rais, Mazniha Berahim

“…This study proposed the use of the Random Forest method to build a predictive model of overspending behaviour among Malaysian households in the B40, M40, and T20 income groups. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

“…Experimental chamber for image acquisition is developed in building the image dataset. 40 random samples of "Mangga Susu Gold Thai mangos are sampled. …”
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Enhanced multi-agent approaches for efficient evacuation and rescue operations in managing disasters by Abusalama, Jawad

“…Notably, as the number of bidders increased, the execution time of competing approaches escalated exponentially, while the proposed approaches exhibited a steady increase. Building on the proposed algorithm and approaches, Agent-Based Simulation (ABS) models were developed to evaluate both evacuation and rescue operations in Al-Aqsa Mosque (AM) scenarios in Palestine. …”
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Green building factor in machine learning based condominium price prediction by Masrom, S., Mohd, T., Rahman, A.S.A.

“…The negative impact of massive urban development promotes the inclusion of green building aspects in the real estate and property industries. …”
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Focal and non-focal epilepsy localization: a review by Hussein, Ahmed Faeq, N., Arunkumar, Gomes, Gorakanage Arosha Chandima, Alzubaidi, Abbas K., Habash, Qais Ahmed, Granados, Luz Santamaria, Moreno, Juan Francisco Mendoza, Gonzalez, Gustavo Ramirez

“…Various methodical and algorithmic studies have indicated that the transition to an ictal state is not a random process, and the build-up can lead to epileptic seizures. …”
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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.

GPS-less Localization Protocol for Underwater Acoustic Networks by Othman, A.K.

“…Four different algorithms have been investigated; (i) Farthest/Farthest Algorithm, (ii) Farthest/Nearest Algorithm, (iii) Nearest/Farthest Algorithm and (iv) Nearest/Nearest Algorithm. …”
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INDOOR LOCATION SENSING USING WLAN by MOORTHY, SATHIS KUMAR

“…The basic idea was to build a database of signal strength information for various predetermined locations. …”
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Design and development of cooperative simultaneous localization and mapping integrated with neural network for mobile robot by Jamaludin, Amirul

“…Secondly, a framework of CSLAM algorithm integrated with ANN using Rao-Blackwellized particle filter (RBPF) algorithm for single SLAM robot, and the map merging using random sample consensus (RANSAC) algorithm, is designed and developed. …”
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A new intelligent multilayer framework for insider threat detection by Ahmad, Rabiah, Al-Mhiqani, Mohammed Nasser Ahmed, Zainal Abidin, Zaheera, Abdulkareem, Karrar Hameed, Mohammed, Mazin Abed, Gupta, Deepak K., Shankar K.

“…For the second layer, a hybrid insider threat detection method has been proposed, where the Misuse Insider Threat Detection (MITD) model has been created using the random forest algorithm. Subsequently, using the K-Nearest Neighbors algorithm, an anomaly insider threat detection algorithm has been developed. …”
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Investigation and analysis of crack detection using UAV and CNN: A case study of Hospital Raja Permaisuri Bainun by Goh, Wei Sheng, Wan Din, Wan Isni Sofiah, Waseem, Quadri, Zabidi, A.

“…Unmanned Aerial Vehicles (UAV) can automate, avoid visual inspection, and avoid other physical check-ups of these buildings. Automated crack detection using Machine Learning Algorithms (MLA), especially a Conventional Neural Network (CNN), along with an Unmanned Aerial Vehicle (UAV), can be effective and both can efficiently work together to detect the cracks in buildings using image processing techniques. …”
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Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad by Ja’afar, Nur Shahirah, Mohamad, Junainah

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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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