dynamic algorithm

dynamic algorithm

[dī¦nam·ik ′al·gə‚rith·əm]
(computer science)
An algorithm whose operation is, to some extent, unpredictable in advance, generally because it contains logical decisions that are made on the basis of quantities computed during the course of the algorithm. Also known as heuristic algorithm.
References in periodicals archive ?
Similar advantages are seen in power inverters for alternative energy systems, which achieve peak efficiency through Maximum Power Point Tracking (MPPT) algorithms and dynamic algorithm adjustments when the wind speed drops or the sky becomes cloudy.
Extensive performance analysis based on the model metrics presented, demonstrated by simulation, the applicability of both the proposed model and the dynamic algorithm in Cluster computing.
Dynamic algorithm to obtain multiple digital signatures of an image.
It interleaves multiple channels like email, texting and social media messaging for campaign communication, driven by a dynamic algorithm underneath, that scores each prospect and adapts to different messaging and channels over time based on the level of recruit's interest.
The Tera Bitcoin Price Index employs a dynamic algorithm that compiles and filters data on a real-time basis from a number of widely utilized global bitcoin exchanges.
This dynamic algorithm enables Zestar to adjust recommendations in real-time to keep users on track to achieve long-term weight loss goals.
The world's leading solar inverter manufacturers -- the majority of which use TI DSCs -- maximize their systems to peak efficiency through Maximum Power Point Tracking (MPPT) algorithms and dynamic algorithm adjustments during various load conditions, including cloudy and low light days.
With this new technology, HP introduces the ability to intelligently translate, or map, any host block address to any disk address with a dynamic algorithm and to change the translation while the system is operating.
The dynamic algorithm also adjusts bandwidth allocation across the number of 802.
The presentations discuss such topics as visualization of non-vectorial data using twin kernel embedding, dynamic algorithm selection using reinforcement learning, mining better technical trading strategies with genetic algorithms, finding the right features for instrument classification of classical music, quantification of intermarket influence based on global optimization and its application for stock market prediction, efficient fuzzy rules for classification, and computational quantification of trust updates, among others.
Furthermore, in order to enhance prediction accuracy, a dynamic algorithm based on the Kalman filter is developed.
In dynamic algorithm the lightest server in the whole network or system is searched and preferred for balancing a load.

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