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Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

“…NMS is also able to find good PID parameters for SISO with lesser performance index, however not able to find better solution in MIMO control. …”
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A METAHEURISTIC OPTIMIZATION ALGORITHM INSPIRED BY TREE PHYSIOLOGICAL SYSTEM by ABDUL HALIM, ABDUL HANIF

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Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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Online PID controller tuning using tree physiology optimization by Halim, A.H., Ismail, I.

“…In the proposed method, every possible solution denoted as tree-shoots is driven by variables from the root system. …”
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Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments by Jauwairia Nasir, Fahad Islam, Yasar Ayaz

“…Rapidly Exploring Random Trees (RRT) are regarded as one of the most efficient tools for planning feasible paths for mobile robots in complex obstacle cluttered environments. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

“…The parameters setting to run the hybrid TS-SBA was determined by using a combination of Factorial Design of Experiments and Decision Tree Data Mining methods. …”
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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

“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms by Fawzi S., Din N.M.

“…In this work meta heuristic algorithm is incorporated at the SDN central controller in a fat tree-based data centre for bandwidth usage monitoring, sleep decisions and path selection using Mininet emulation. …”

Predicting open space parking vacancies using machine learning by Lee, Wei Jun

“…In this project, two additional machine learning algorithms, namely linear regression (LR) and decision tree regressor, were used to compare the performance of the support vector regression (SVR) prediction model. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…Moreover, the study provided systematic solutions based on reconfiguring the pedestrian zone by the trees. …”
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Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction by Yafouz A., AlDahoul N., Birima A.H., Ahmed A.N., Sherif M., Sefelnasr A., Allawi M.F., Elshafie A.

Machine learning‐based approach for bandwidth and frequency prediction of circular SIW antenna by Alam, Md Mahabub, Nurhafizah, Abu Talip Yusof, Ahmad Afif, Mohd Faudzi, Tomal, Md Raihanul Islam, Haque, Md Ershadul, Rahman, Md. Suaibur

“…A predictive ML framework was developed using six regression algorithms trained on significant geometrical parameters, such as ring slot radius, via diameter, and feedline width. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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