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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…The ECDRQ Routing Algorithm integrates the ECQ and Dual Reinforcement Q (DRQ) Routing Algorithms with Alternative Q Value Approach to minimise the effect of partially learning cycle. …”
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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 the cycle of Industrial Revolution 4.0 (IR 4.0), many issues in the industries can be solved with implementation of artificial intelligence approaches, including machine learning models. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…To address these problems, this paper introduces a novel hybrid approach for RUL prediction, combining a Lightning Search Algorithm (LSA) with a Long-Short Term Memory (LSTM) deep learning model. …”

Improving forest above-ground biomass estimation by integrating individual machine learning models by Luo, Mi, Ahmad Anees, Shoaib, Huang, Qiuyan, Qin, Xin, Qin, Zhihao, Fan, Jianlong, Han, Guangping, Zhang, Liguo, Mohd Shafri, Helmi Zulhaidi

“…The accurate estimation of forest above-ground biomass (AGB) is crucial for sustainable forest management and tracking the carbon cycle of forest ecosystem. Machine learning algorithms have been proven to have great potential in forest AGB estimation with remote sensing data. …”
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Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

An artificial neural network approach in service life prediction of building components in Malaysia based on local environment and building service load by Tapsir, Siti Hamisah, Mohd. Yatim, Jamaludin, Usman, Fathoni

“…The back-propagation learning algorithm is used as learning model. The environment load factors, workmanship, design, usage and level of maintenance are used as input variables in training process of the neural network model. …”
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Application of computational intelligence methods in modelling river flow prediction: A review by Zaini N., Malek M.A., Yusoff M.

Ultrasound-assisted process optimization and tribological characteristics of biodiesel from palm-sesame oil via response surface methodology and extreme learning machine - Cuckoo s... by Mujtaba, M. A., Masjuki, Haji Hassan, Kalam, Mohammad Abul, Ong, Hwai Chyuan, Gul, M., Farooq, Muhammad, Soudagar, Manzoore Elahi M, Ahmed, Waqar, Harith, M. H., Yusoff, Mohammad N.A.M.

“…The purpose of this study was the improvement of cold flow and lubricity characteristics of biodiesel produced from the palm-sesame oil blend. Extreme learning machine (ELM) and response surface methodology (RSM) techniques were used to model the production process and the input variables (time, catalyst amount, methanol to oil ratio, and duty cycle) were optimized using cuckoo search algorithm. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. …”
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Development of machine learning models for estimation of daily evaporation and mean temperature: a case study in New Delhi, India by Rajput J., Kushwaha N.L., Srivastava A., Pande C.B., Suna T., Sena D.R., Singh D.K., Mishra A.K., Sahoo P.K., Elbeltagi A.