Sentence examples for using the soft computing from inspiring English sources

Extensive comparison is made using the soft computing approaches for noise cancellation based on associative memories.

Optimal design of arch dams including dam-water foundation rock interaction is achievedam-water foundationputing techniques.

This work investigates the process of yield prediction in cotton crop production using the soft computing technique of fuzzy cognitive maps.

Concluding, our scope is to present a new methodology through a framework for decision making tasks using the soft computing technique of FCMs based on knowledge extraction methods.

The importance of using the soft computing techniques is generally clarified, as long as non-linear systems and also complex physical structures can all be modeled more precisely and flexibly, at a lower cost, and, in a shorter period of time, so they match with elite human decisions, in a high correctness percentage.

This field leads to provide the combination of methods that can be used to represent a set of complex systems in modeling of which is impossible or very hard by applying computational regulations of pure mathematics and hard logic to them, whilst the applicable simulations and practical implementations may be conducted by using the soft computing techniques.

Authors used the soft computing method of fuzzy cognitive maps to represent and model experts knowledge of the FCM grading model.

The costly and time-consuming determination of thermophysical properties of nanofluids through the experimental analysis leads the current investigations to use the soft computing methods like correlating, artificial neural network (ANN) and genetic algorithm.

The comparative performance evaluation was done among the existing charging control methods and the proposed system, which demonstrated a significant increase of performance (minimum charging time and minimum overheating) using the soft computing-based approach.

To avoid the analytical model in this article soft computing approach was used since the soft computing approach does not require internal knowledge of the vibration model.

In contrast to using the conventional soft computing methods, this study proposes two emerging soft computing techniques, extreme learning machine (ELM) and random forest (RF), to address the difficulties for recognition of embedded disturbance patterns in the control charts.