"adjust dynamically" is a correct and usable phrase in written English.
It means to make changes or modifications in a variable or flexible manner, usually in response to changing conditions or circumstances. Example: The software program is designed to adjust dynamically to the user's preferences, providing a personalized experience for each individual.
Secondly, Bayesian approach is adopted to adjust dynamically the calculated results of static identification model.
Instead, the aim should be to use processes and measures that help the business to adjust dynamically to changes in the real world.
Distributed computer control systems used nowadays in the industry need often to meet requirements of on-line reconfigurability so they can adjust dynamically to changes in the application environment or to evolving specifications.
The model will adjust dynamically the measurement frequency of files based on the measurement result.
For example, if you are driving on a high-way and wish to stop and grab a bite to eat or fill the car with gas, the GPS interface not only will point you to the nearest restaurant or gas station, but your dashboard will also adjust dynamically. .
The new player brings a few firsts to live video: an adaptive bitrate which can adjust dynamically based on the viewers bandwidth up to HD quality (720p); an instant playback DVR feature; a live blogging platform to add text, photos, and video clips underneath the main video; and social networking features.
Recently, it is shown that adjustable delay buffer (ADB) whose delay can be adjusted dynamically can solve the clock skew variation problem effectively.
To enhance the perceptual quality the buffering delay should be adjusted dynamically throughout the vocal conversation.
The probability of crossover and mutation are adjusted dynamically according to the generation number and the fitness value.
After the initial weight distribution is determined, the weights of the basic trading rules will adjusted dynamically every day in the trading process using particle swarm optimization algorithms.
And, crossover probability and mutation probability are adjusted dynamically by fuzzy inferences, which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.
