15 results about "Feedback analysis" patented technology

The embodiment of the application discloses a method and system for detecting the state of a bone conduction hearing device, the bone conduction hearing device at least comprising a microphone, a speaker, a feedback analysis unit and a signal processing unit, the method comprising: generating a third sound by the speaker based on a first signal; wherein the first signal is generated by the signal processing unit; receiving the third sound by the microphone and generating a feedback signal; determining, by the feedback analysis unit, the feedback path transfer function from the speaker to the microphone of the bone conduction hearing device based on the feedback signal of the microphone and the first signal; obtaining at least one preset feedback path transfer function; comparing the feedback path transfer function with the at least one preset feedback path transfer function; and determining, by the signal processing unit, the state of the bone conduction hearing device according to the comparison result.

This invention relates to the fields of industrial automation control and smart water management, and discloses a multi-mode adaptive scheduling method for pump stations based on water volume prediction and dynamic optimization. The method includes: calculating the predicted water demand using an LSTM water volume prediction module combined with real-time meteorological characteristics; generating an optimal scheduling instruction set through a particle swarm optimization module with the goal of minimizing total system energy consumption; parsing the instructions and activating the corresponding control mode at the field control terminal, driving the pumps using a strategy combining feedforward compensation and PID control; and adaptively correcting the optimization model parameters using actual operating deviations using a closed-loop feedback analysis module. The system includes a water supply pump unit, a pipeline operation data sensing unit, a field control terminal, and an edge computing decision-making unit. This invention solves the problems of traditional control lag and model distortion, achieving global energy consumption optimization and high-precision stable control of the pump station.

This invention discloses a method and system for certificate generation and delivery in the field of big data processing, specifically for certificate-related business. The method includes the following steps: collecting original photos and user identification identifiers; generating processed ID photos, original photo hashes, processed ID photo hashes, cropped rectangle coordinates, and calculated photo specifications; binding the processed ID photos to the user identification identifiers; determining available cloud-based ID photos; generating certificate PDFs and associated data; collecting and correcting printed images; performing dual-benchmark verification and photo visual quality feedback analysis; generating dual-benchmark verification results and photo visual quality feedback results; and generating delivery instructions or rollback instructions. This invention achieves consistent photo specifications in PDFs and distinguishes and allows for targeted rollback of abnormal sources by establishing a cloud-based photo source traceability and dual-benchmark verification mechanism. It solves the problems of inherited, amplified, or incorrectly attributed photo generation deviations in existing technologies.

The application discloses a deep learning-based adaptive prediction and ammonia injection flow field optimization method and system, and relates to the technical field of automatic ammonia injection. The deep learning-based adaptive prediction and ammonia injection flow field optimization method comprises the following steps: S1, collecting working condition data and emission monitoring data in the ammonia injection process, storing the data after preprocessing, and constructing an ammonia injection operation and maintenance database; S2, constructing an emission prediction model by adopting a recurrent neural network and a particle swarm optimization algorithm on training samples, performing precision evaluation on prediction errors, executing updating, and outputting prediction results; S3, performing ammonia injection optimization control analysis by using emission prediction data and ammonia escape amount; and S4, optimizing the ammonia injection strategy and adjusting the emission prediction model according to the correction feedback analysis result. The problems of the decrease of denitration efficiency, the non-standard emission and the serious ammonia escape phenomenon caused by the temperature and pressure parameter fluctuation in the combustion process are solved.

Systems and methods for a feedback analysis system to identify a sentiment associated with user feedback (e.g., notes) and generates a task based on the identified sentiment. Specifically, the feedback analysis system as described herein may receive user feedback corresponding to a contract job and provide the user feedback as input into a large language model to identify a sentiment associated with the user feedback. In response to the user feedback as input, the feedback analysis system may synthesize, based on the identified sentiment of the user feedback, a summarized sentiment, wherein the summarized sentiment indicates a level of satisfaction associated with a performance of the contract job. In some embodiments, the feedback analysis system generates a task based on the user feedback and the summarized sentiment, wherein the task is one of a notification, an alert, an update, or an automated process related to the contract job.

The application provides an intelligent prevention and control method and system for methanol vapor diffusion of a ship, the method comprising: collecting operation data of vapor concentration, fuel storage and equipment vibration in the methanol fuel transportation process; constructing a methanol vapor diffusion prediction model according to the collected operation data combined with the ship navigation state and environmental parameters; generating a methanol vapor diffusion path and a corresponding risk level based on the prediction model; formulating a ventilation and fuel transportation control strategy according to the risk level, and sending control instructions to a ventilation linkage control subsystem and a methanol fuel transportation subsystem; executing the control instructions, performing feedback analysis on the control results, and forming a closed-loop correction; storing and analyzing the data in the prevention and control process for safety evaluation and pollutant emission and carbon emission reduction effect evaluation. The application realizes the transformation from passive alarm to active prevention and control, and significantly improves the safety, environmental protection and operation reliability of the methanol fuel ship.

This invention discloses an intelligent electro-pulse therapy control method based on AI adaptive feedback, relating to the field of electro-pulse therapy control. The method includes the following steps: collecting biofeedback signals from the therapy user and simultaneously collecting the user's subjective feedback data; converting the subjective feedback data into effective subjective data and performing preliminary analysis of the feedback analysis data between different biofeedback signals and subjective feedback data; deeply analyzing the influence of different biofeedback signals on the subjective feedback data, and simultaneously constructing historical reference analysis schemes and predictive reference analysis schemes to calibrate the impact on the feedback analysis data, obtaining feedback reference data; and intelligently controlling the intelligent electro-pulse therapy based on the feedback reference data. This invention addresses the problem that existing electro-pulse therapy control technologies lack intelligent and accurate acquisition of pain perception, resulting in an inability to adjust the intensity of the electro-pulse in a timely and accurate manner.

The application provides a kind of intelligent ship broadcast and alarm system and method, system includes: distributed intelligent acoustic terminal network, fusion perception internet of things, central intelligent processing platform and immersive command console.Central intelligent processing platform contains digital twin ship model engine, intelligent alarm and broadcast strategy engine, adaptive broadcast optimization module and two-way communication and feedback analysis module.Through real-time acquisition of shipboard environmental noise, sensor alarm and personnel distribution data, fusion and visualization are carried out in the digital twin model;When receiving sensor alarm, intelligent strategy engine automatically generates broadcast strategy containing target area list and customized voice text;Adaptive broadcast optimization module calculates optimized audio parameters according to real-time environmental noise;Instructions are issued to intelligent terminal for accurate broadcasting;The system receives on-site personnel state feedback and updates the digital twin model in real time, significantly improving the accuracy, efficiency and intelligence level of ship emergency command.

An adaptive conversational content generation system utilizes advanced technologies to provide personalized, dynamic, and emotionally intelligent interactions through a virtual voice assistant. Central to the system is a cloud server that hosts an adaptive conversational content generation service, allowing the assistant to create real-time, context-aware content based on a user's personalized profile. Key components, such as the conversation simulator, feedback analysis unit, and emotional empathy cues unit, enable the system to engage users in empathetic, meaningful conversations. Additionally, the integration of predictive modeling and conflict resolution units ensures the assistant can proactively anticipate user needs and mediate emotional conflicts. The system supports multilingual interactions, enhancing accessibility across diverse linguistic and cultural backgrounds. The system adapts to network conditions, ensuring seamless functionality. The use of Generative Adversarial Networks further refines conversational authenticity, enabling the assistant to mimic nuanced human speech patterns for more natural, emotionally resonant interactions.

The present application relates to a large model intelligent agent Prompt optimization method, system and device, belonging to the field of artificial intelligence. The method comprises: receiving an initial Prompt and extracting semantic features; intelligently recommending optimization templates, frameworks or models from a resource library based on the features; generating an optimized Prompt using the recommended resources; calling multiple large model intelligent agents to actively evaluate the Prompt and generate feedback suggestion labels; and iteratively optimizing based on user feedback. The system includes four core modules: input processing and version management, intelligent recommendation, generation optimization, feedback analysis and active mining. The present application realizes the tracing and management of the optimization process by constructing a version evolution graph that records the optimization semantic link, accurately matches optimization resources through intelligent recommendation driven by semantic features, and effectively solves the problems of chaotic Prompt optimization process, low efficiency and dependence on expert experience in the prior art through fuzzy feedback analysis and multi-agent active evaluation optimization of human-computer collaboration, thereby improving the automation level and quality of Prompt optimization.

This invention relates to the field of cold-end control technology for generator units, and particularly to a cold-end optimized control system for generator units based on a real-time twin model. The system includes a cold-end management platform, a cooling information unit, a performance evaluation unit, an energy-saving evaluation unit, a sequence control unit, a start-stop adjustment unit, and a control response unit. This invention analyzes the system from two perspectives: energy-saving operation and regulation control, to ensure the low-consumption and high-efficiency operation of the generator unit's cold-end equipment and the sensitivity of the cold-end control system. It uses information feedback to perform operational sequence control feedback analysis on state loss data, enabling subsequent reasonable control of the operating sequence of the generator unit's cold-end equipment to ensure the overall stability of the cold-end operation. Simultaneously, it performs detailed evaluation and adjustment of operating temperature data to prevent prolonged use or abnormal operation of any generator unit's cold-end equipment, thus avoiding increased risk of damage and ultimately helping to extend the service life of the generator unit's cold-end.

The application relates to the field of operation and maintenance analysis, and discloses an intelligent operation and maintenance method for an industrial reverse osmosis system based on edge computing, which realizes real-time collection of reverse osmosis system operation data through an edge computing node, forms an operation parameter data set after pretreatment, inputs the data set into a first prediction model to predict short-term change values of key parameters, selects a verification mode according to real-time operation conditions of the system to logically verify the first prediction result, inputs the verified result into a second prediction model to obtain a comprehensive health index, obtains an operation and maintenance decision index by fusing the double prediction results, generates differentiated operation and maintenance guidance decisions of continuous monitoring, optimized adjustment, preventive maintenance or immediate intervention, and outputs a targeted fault diagnosis result after triggering a parameter feedback analysis mechanism to locate abnormal parameters and replacing the abnormal parameters with historical statistical values for re-verification if the verification fails. The application solves problems such as lagging response of traditional operation and maintenance and inaccurate prediction, improves system operation stability, and reduces operation and maintenance cost.

This invention discloses a method for dynamically adjusting grouting parameters during segmented grouting of horizontal holes. First, before grouting, the horizontal hole is divided into multiple independent grouting segments along its axial direction based on its length, surrounding rock conditions, and construction requirements. Then, initial grouting parameters for each segment are set, and trial grouting is performed. Next, the grouting process parameters are monitored and dynamically evaluated in real time to determine if the grouting process is stable. Then, based on identified abnormal changes, the grouting parameters are dynamically adjusted, and corresponding construction adjustment measures are implemented. Finally, the grouting effect of the segment is comprehensively analyzed, and the grouting parameters for subsequent segments are corrected and optimized based on the feedback analysis results. This application features seamless and coordinated closed-loop processes, abandoning the traditional experience-based extensive construction mode, significantly improving grouting controllability, construction safety, and the uniformity of overall formation reinforcement and water plugging, thereby greatly improving grouting quality.

Disclosed is a technology which dynamically switches a fast-thinking LLM and a slow-thinking LLM and optimizes the time and accuracy of an AI response through automated user feedback analysis. An AI-based response system provides a prompt response by using the fast-thinking LLM on a user request, and when a complicated query or negative feedback is detected, switches to the slow-thinking LLM to generate a more accurate response. Also, the system asynchronously improves performance of the fast-thinking LLM by using a result of the slow-thinking LLM and user feedback, and thus, decreases the frequency number of model switching and enhances response quality. An AI agent used in sleep consultation is proposed.