Search Results - intelligence valid ((tree algorithm) OR (_ algorithm))

Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Finally, the proposed algorithms were also validated on another dataset of a university campus in a different region. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Application of sampling-based motion planning algorithms in autonomous vehicle navigation by Khaksar, Weria, Mohamed Sahari, Khairul Salleh, Tang, Sai Hong

“…The performance of the proposed method is tested through simulation in different scenarios and also by comparing the performances of RRT and RRT* algorithms. The proposed method provides near-optimal solutions with smaller trees and in lower running time.…”
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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

“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Neutralisation state driven single-agent search strategy for solving constraint satisfaction problem / Saajid Akram Ahmed Abuluaih by Ahmed Abuluaih, Saajid Akram

“…Since Constraint Satisfaction Problem (CSP) is an NP-complete problem, brute-force search algorithms such as Backtracking algorithm (BT) are required as the guarantee to find a solution, when there is one. …”
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Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

“…These rules would then be compared with and validated by benchmarking decision-tree-based data-mining analysis.…”
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Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…The result revealed that the ANN performance had the highest accuracy when training using the LM training algorithm. The ANN with the seven inputs (seven significant compounds from Z-score pre-processing technique) trained by one hidden neuron of LM algorithm provided the best performance with 100% for accuracy, specificity, sensitivity and precision as well as minimum convergence epoch.…”
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Automatic detection of oil palm tree from UAV images based on the deep learning method by Xinni, Liu, Kamarul Hawari, Ghazali, Fengrong, Han, Izzeldin, I. Mohd

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Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

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Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…Furthermore, Random Forest is compared to four machine learning algorithms including Support Vector Machine, XGBoost, Convolutional Neural Networks, and Decision Trees. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…The integration of artificial intelligence techniques is becoming necessary for environmental risk assessment systems and decision-making, particularly under the limitations of individual intelligence techniques. …”