A hybrid model in dynamic software updating for c
Forecasting Baltic Panamax Index with Support Vector Machine. A Scaled conjugate gradient algorithm for fast supervised learning. International Journal of Computational Intelligence Systems. Engineering Applications of Artificial Intelligence. Prediction intervals to account for uncertainties in neural network predictions: Methodology and application in bus travel time prediction. Physica A: Statistical Mechanics and its Applications. LS Nav 2018 will be released in January 2018, and will employ the same technology and code as LS Nav 2017 (which is currently available, and will be supported until the end of 2021).LS Nav 2018 will also support the Events and Extensions technology, which enables third parties to easily add and preserve their customizations to the system.LS Nav 365 (on Microsoft Dynamics 365 Tenerife) is expected in the spring of 2018.LS Nav 365 will be totally integrated with other products in the Microsoft stack; this means you will be able to work with products such as Office 365, Power BI, Power Apps, Cortana, and more.
An improved support vector machine (SVM) is applied in this paper to predict bus travel time and then the efficiency of the improved SVM is checked. A Dynamic Bus-Arrival Time Prediction Model Based on APC Data. Acevedo-Rodríguez J, Maldonado-Bascón S, Lafuente-Arroyo S, Siegmann P, López-Ferreras F.
Neighborhood rough set and SVM based hybrid credit scoring classifier.
Efficient computations for large least square support vector machine classifiers.
Predicting defect-prone software modules using support vector machines.
Bus Arrival Time Prediction Using Support Vector Machines.