WiMi Hologram Cloud Inc., a leading global Hologram Augmented Reality (AR) Technology provider, announced that a real-time data-driven multi-objective evolutionary algorithm was developed, multi-objective evolutionary algorithm is an algorithm suitable for solving multi-objective optimization problems, which can find the optimal equilibrium between multiple objectives.Different from the traditional single-objective optimization algorithm, the multi-objective evolutionary algorithm can consider multiple objectives at the same time, thus obtaining more comprehensive and accurate results.The real-time data-driven multi-objective evolutionary algorithm integrates real-time data into the algorithm, and realizes the adaptive and real-time nature of the algorithm by constantly updating the data and parameters.
The algorithm is a powerful search tool, and its core idea is based on the evolutionary algorithm for multi-objective optimization driven by real-time data, and the algorithm usually consists of the steps of data collection, problem instantiation, algorithm solving, and model updating.
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The data are first obtained from the real-time data stream and are pre-processed and feature extracted. The pre-processed data is converted into a problem instance and a multi-objective optimization model is constructed. Then use the multi-objective evolutionary algorithm to solve the problem instances and get the optimal solution. And use the optimal solution to update the multi-objective optimization model and regenerate the next round of problem instances based on the new model.
Real-time data-driven multi-objective evolutionary algorithm can help people better solve multi-objective optimization problems in complex and dynamic environments by combining the advantages of the real-time data and evolutionary algorithm. It has a strong adaptive ability and can be adjusted according to different problems and data.In different environments, different evolutionary strategies can be chosen to adapt to different changes. With the real-time data-driven multi-objective evolutionary algorithm, it can effectively deal with complex, nonlinear systems and maintain robustness and reliability in dynamic environments. It not only runs on single-core computers, but can also be applied in environments such as high-performance computer systems, distributed computing and cloud computing. Compared with other intelligent algorithms, the real-time data-driven multi-objective evolutionary algorithm is easier to explain and understand.
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WiMi‘s real-time data-driven multi-objective evolutionary algorithm has been widely used in many fields, such as intelligent transportation systems, industrial automation, finance and healthcare. These applications involve a large amount of real-time data streams, which are difficult for traditional optimization algorithms to handle efficiently. The real-time data-driven multi-objective evolutionary algorithm can continuously sample and process data streams through online real-time execution, and can help us quickly respond to changing data streams, identify and solve practical problems promptly, and continuously iteratively optimize models and algorithms so as to improve efficiency and accuracy. It can also consider multiple objectives at the same time, such as cost, efficiency, accuracy, etc., providing powerful decision support for decision-makers in various industries.
In the future, with the increasing digitization of various industries, large-scale real-time data streaming will become mainstream. The real-time data-driven multi-objective evolutionary algorithm, as an optimization technique based on the evolutionary algorithm and real-time data streams, has the advantages of being easy to implement, high reliability, and strong performance, so its application prospects are very broad. In the future, with the continuous improvement and refinement of the algorithm, it will be applied in more fields, such as smart manufacturing, smart city, Internet of Things, etc., to make greater contributions to promoting the digital transformation and upgrading of various industries.
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