4 results about "Efficient algorithm" patented technology

This application relates to an unsupervised multimodal data fusion method for medical diagnosis. The method preprocesses each modality of data in all samples to obtain first image features, first text features, and first physiological features. These first image features, first text features, and first physiological features from each training sample are then input into a variational autoencoder (VAE) and a generative adversarial network (GAN) to train the VAE and GAN respectively. Finally, any multimodal data to be fused is sequentially passed through the trained VAE and GAN to output the second features of the corresponding modality. The second features of each modality are then fused to obtain the final fused feature. This method, in an unsupervised environment, designs an efficient algorithm capable of simultaneously processing and fusing different medical modalities, providing richer semantic knowledge representations for complex tasks.

This invention discloses a cross-modal retrieval and precise recommendation method for industrial algorithm marketplaces, comprising: collecting candidate algorithm data and user behavior data; generating algorithm feature vectors and user demand feature vectors, mapping them to generate standardized input feature vectors; constructing algorithm call adjacency sequences and algorithm industry association sequences; constructing an improved liquid state machine model and setting connection paths for the industry association sequences; constructing and optimizing an adaptive differential evolution algorithm model; inputting the standardized feature vectors into the optimized liquid state machine model to generate dynamic semantic state representations; performing similarity matching between the query dynamic state representations and the dynamic semantic state representations of candidate algorithms to generate initial retrieval results; reweighting and outputting personalized recommendation results. This invention achieves efficient algorithm model optimization for cross-modal retrieval and precise recommendation, improves recommendation accuracy and personalized services, and is applicable to intelligent recommendation scenarios in multiple fields.

This invention discloses a current optimization method for electrolytic copper based on a non-dominated sorting genetic algorithm. The method includes establishing a sub-model of a multi-objective optimization problem in the electrolytic copper production process; establishing a prediction model for the concentration of key ions in the electrolytic cell based on the principle of mass conservation; setting production process constraints, including at least the maximum rectifier current constraint and daily output target constraint, and transforming the constrained multi-objective optimization problem into an unconstrained optimization problem through a penalty function; and solving the unconstrained optimization problem using a non-dominated sorting genetic algorithm, outputting a sequence of optimal current values ​​for each time period within the next 24 hours, in units of a set time interval. This invention, by constructing a multi-objective model that integrates ion concentration prediction and employing an efficient algorithm for solving it, can achieve refined and collaborative optimization of the current in the electrolytic copper production process, thereby effectively reducing electricity costs while ensuring both output and quality.

A computer system for efficient computation of decay velocity in a distributed computing system. The computer system includes a memory device in communication with a processor. The processor is programmed to receive transaction information of transactions of one or more cardholders within a payment network. The transaction information includes data relating to purchases made by the cardholders at one or more merchants. The computer system determines a decay velocity of the transactions based on one or more time quantities without the need to separately group and sort dimensions of the transactions.