Search results
Results from the WOW.Com Content Network
The most important aspect of any hot working process is controlling the temperature of the workpiece. 90% of the energy imparted into the workpiece is converted into heat. Therefore, if the deformation process is quick enough the temperature of the workpiece should rise, however, this does not usually happen in practice.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
scikit-learn, an open source machine learning library for Python; Orange, a free data mining software suite, module Orange.ensemble; Weka is a machine learning set of tools that offers variate implementations of boosting algorithms like AdaBoost and LogitBoost
Hot extrusion is a hot working process, which means it is done above the material's recrystallization temperature to keep the material from work hardening and to make it easier to push the material through the die. Most hot extrusions are done on horizontal hydraulic presses that range from 230 to 11,000 metric tons (250 to 12,130 short tons ...
Rotary piercing is a hot working metalworking process for forming thick-walled seamless tubing. There are two types: the Mannesmann process, invented in the 1880s, and the Stiefel process, developed two decades later. [1]
The working substance can be any system with a non-zero heat capacity, but it usually is a gas or liquid. During this process, some heat is normally lost to the surroundings and is not converted to work. Also, some energy is unusable because of friction and drag. In general, an engine is any machine that converts energy to mechanical work.
Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is ...
In control applications, two types are distinguished: Moore machine The FSM uses only entry actions, i.e., output depends only on state. The advantage of the Moore model is a simplification of the behaviour. Consider an elevator door. The state machine recognizes two commands: "command_open" and "command_close", which trigger state changes.