Results 271 to 280 of about 350,996 (311)

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Intrusion detection system based on machine learning using least square support vector machine. [PDF]

Sci Rep
Waghmode P, Kanumuri M, El-Ocla H, Boyle T.   +3 more
europepmc   +1 more source

3D‐Printing Aided Rapid Prototyping of Pretensioned Tensegrity Structures for Robotic Applications

Advanced Robotics Research, EarlyView.
Printing, injection molding, and assembly (PMA) is a method for rapid prototyping mesoscale, topologically complex, and tensioned tensegrity structures. In combination with PMA method, two mold design strategies: modular mold and compact channel layout, enable efficiency and scalability for tensegrity fabrication.
Yi Sun, Jan Petrš, Omar Aloui, Dario Floreano   +3 more
wiley   +1 more source

Heat treatment control technology of high-strength steel gears based on support vector machine. [PDF]

Sci Rep
Wang Y, Zhang L, Su Y, Liu H, Yang H, Chen Y.   +5 more
europepmc   +1 more source

Enhanced brain image security using a hybrid of lifting wavelet transform and support vector machine. [PDF]

Sci Rep
Mohamed AF, Samra AS, Yousif B, Tawkol Khalil A.   +3 more
europepmc   +1 more source

Identifying network state-based Parkinson's disease subtypes using clustering and support vector machine models. [PDF]

Front Psychiatry
Nguchu BA, Han Y, Wang Y, Shaw P.
europepmc   +1 more source

Exploring the relationship between annual soil loss and formation rate in different land use scenarios using support vector machine (SVM) learning models in Tigray Highlands. [PDF]

Sci Rep
Haftu M, Gidey E, Mhangara P, Dikinya O.
europepmc   +1 more source

[Application of support vector machine in identifying neuromodulation states in patients with zoster-associated pain]. [PDF]

Zhong Nan Da Xue Xue Bao Yi Xue Ban
Chen L, Wu Q, Zhou H, Liu S.
europepmc   +1 more source

Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest. [PDF]

Front Neurol
Wu Q, Zhang F, Fei Y, Sima Z, Gong S, Tong Q, Jiao Q, Wu H, Gong J.   +8 more
europepmc   +1 more source

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Support vector machines in A+

ACM SIGAPL APL Quote Quad, 2004
This paper considers the implementation of Support Vector Machines (SVM), the new extensive class of data analysis methods. SVM have a number of advantages as compared with standard data mining techniques like artificial neural networks, for example. In the paper this methodology is described in details and implemented in A+ programming language in the
Alexander O. Skomorokhov, Alexander Nakhabov   +1 more
openaire   +1 more source