Search Results - (( re evaluation step algorithm ) OR ( parameter adaptation tree algorithm ))*

Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments by Jauwairia Nasir, Fahad Islam, Yasar Ayaz

“…This paper presents a new scheme for RRT*-Smart that helps it to adapt to various types of environments by tuning its parameters during planning based on the information gathered online. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

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A negotiation algorithm for decision-making in the construction domain by Idrus A., Mahmoud M.A., Ahmad M.S., Yahya A., Husen H.

Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer by Hilo, Ali Kareem, Abu Talib, Abd Rahim, Iborra, Antonio Acosta, Hameed Sultan, Mohamed Thariq, Abdul Hamid, Mohd Faisal

“…Combining the corrugated wall with backward-facing step enhanced the Nusselt number (Nu) up to 62% at Re = 5000. …”
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The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration by Yaseen, Zaher, Ehteram, Mohammad, Sharafati, Ahmad, Shahid, Shamsuddin, Al-Ansari, Nadhir, El-Shafie, Ahmed

“…The LSSVM-BA model results are compared with those obtained using M5 Tree and Multivariate Adaptive Regression Spline (MARS) models to show the efficacy of this novel integrated model. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

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.

Nanofluid flow and heat transfer in corrugated backward-facing step channel using ethylene glycol as based fluid by Hilo, Al Behadili Ali Kareem

“…Combined the backward-facing step with corrugated wall enhanced the Nusselt number (Nu) up to 62% at Re = 5,000. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…The study primarily focuses on tree-based techniques, including Random Forest (RF), Adaptive Boost (ADABoost), Gradient Boosting Tree (GBT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LGBoost), and Categorical Gradient Boosting (CatBoost). …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The Random Tree standalone ML-AP relay model presented the best performing models from the ML-APS relay model with the best average performance for the correctly classified fault types of 97.61 % at 5 % significance level above other ML algorithms. …”
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An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting by Kassim N.M., Santhiran S., Alkahtani A.A., Islam M.A., Tiong S.K., Mohd Yusof M.Y., Amin N.

ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“… • All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided…”
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A Random Forest Regression Based Space Vector PWM Inverter Controller for the Induction Motor Drive by Hannan M.A., Ali J.A., Mohamed A., Uddin M.N.

ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Re: Gen - web-based resume generator with content recommender for it job field / Nurul Syahmina Mohd Khairuddin … [et al.] by Mohd Khairuddin, Nurul Syahmina, Ahmadon, Fadzlin, Hashim, Madihah Hannani, Mohd Vauxhall, Nur Ain Emylia

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Easy to use remote sensing and GIS analysis for landslide risk assessment by Dibs, Hayder, Al-Janabi, Ahmed, Gomes, Gorakanage Arosha Chandima

“…We discussed different type of algorithms and factors for modeling the prediction of landslide risk assessment such as SVM (support vector machine), DT (decision tree), ANFIS (adaptive neural-fuzzy inference system), AHP (analytic hierarchy process), ANN (artificial neural network), probability frequency of landslides occurrence factors model and empirical model. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj by Bryan Raj , Peter Jabaraj

“…Moreover, two improvised clustering techniques are introduced to reduce the energy overhead cost from the re-clustering process. The performance of aHSSOGA is evaluated based on average residual energy, network lifetime, total re-clustering occurrence, total data delivery, network throughput and end-to-end delay metrics. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Finally, the initial partitioning is successively un-coarsened and re-refined back to the original hypergraph. These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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