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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

“…In addition, time and expertise are important factors needed to adapt the model to a specific problem such as green building housing development. Green building is known as a potential method to improve building performance efficiency. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…However, although there are several world-class green buildings built in the recent years, the idea of green building development in Malaysia is only in its infancy. …”
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Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models by Xue, Ruixiang, Ong, Tze San, Demir, Ezgi

“…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms by Murti M.A., Junior R., Ahmed A.N., Elshafie A.

Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

“…Hue, Saturation, Value (HSV) color space was found to be effective for distinguishing between the trees and weeds while the index of subtraction red from green (RG) is useful for separation of soil and greenness objects in tree identification. …”
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Testing the use of machine learning for heritage property valuation / Junainah Mohamad, Nur Shahirah Ja’afar and Suriatini Ismail by Mohamad, Junainah, Ja’afar, Nur Shahirah, Ismail, Suriatini

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Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

“…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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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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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…Based on the X and Z chromaticity data from the chromaticity analysis, the color of the infected chicken�s comb converged from red to green and yellow to blue. The development of the algorithms shows that Logistic Regression, SVM with Linear and Polynomial kernels performed the best with 95% accuracy, followed by SVM-RBF kernel, and KNN with 93% accuracy, Decision Tree with 90% accuracy, and lastly, SVM-Sigmoidal kernel with 83% accuracy. …”

Color recognition wearable device using machine learning for visually impaired person by Bolad, Tarek Mohamed, Nik Hashim, Nik Nur Wahidah, Mohamad Hanif, Noor Hazrin Hany

“…In addition, neural network and decision tree algorithms were trained and tested with eight colors (red, green, blue, orange, yellow, purple, white, and black) for the conversion to sound and vibration. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

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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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

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Ensemble deep learning approach for apple fruitlet detection from digital images by Yusof, Mohamad Yusnisyahmi, Ishak, Iskandar, Sidi, Fatimah

“…Agriculture commodities are commodities that have a high economic worth and the potential to be developed further. The green and red apple, in instance, is one type of fruit that has the potential to be cultivated as part of agriculture. …”
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

Modeling of mechanical properties of silica fume-based green concrete using machine learning techniques by Nafees, A., Amin, M.N., Khan, K., Nazir, K., Ali, M., Javed, M.F., Aslam, F., Musarat, M.A., Vatin, N.I.

“…ML algorithms are used to predict SFC compressive strength to promote the use of green concrete. …”
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