149results about How to "Solve resource problems" patented technology

The invention discloses a multi-terminal vehicle management system based on an intelligent algorithm, relates to the technical field of vehicle management, and is used for solving the problem of insufficient real-time performance and cooperative efficiency of vehicle management. According to the method, a multi-modal sensor fusion technology is combined with Gaussian process regression, complex environment data is modeled in real time, dynamic target and static background features are accurately extracted, environment changes are analyzed and predicted in combination with a time sequence, accurate input is provided for path planning and task allocation, a path is dynamically adjusted through an incremental optimization algorithm, emergencies are coped, and the path planning and task allocation efficiency is improved. According to a distributed path optimization mechanism, multi-vehicle task path conflicts are eliminated, the cooperation efficiency is improved, a priority model is constructed based on the task emergency degree, the time constraint and the resource matching degree, the weight is dynamically adjusted, vehicle and task matching is optimized in combination with reinforcement learning, the task execution efficiency is ensured, resource competition and path conflicts are solved, and the task execution efficiency is improved. Efficient cooperation in a complex dynamic environment is realized, and the real-time performance and management efficiency of vehicle management are improved.

The invention relates to the field of green computing and intelligent computing center management, and discloses a green intelligent computing center computing power dynamic regulation and control method based on carbon emission demand analysis, which comprises the following steps: data acquisition and analysis: acquiring multi-dimensional data of a green intelligent computing center in real time, including carbon emission intensity, server load, energy consumption, environmental conditions and cooling system energy efficiency data, preprocessing and analyzing the data; energy efficiency management and control standards are dynamically generated, the energy efficiency management and control standards of the intelligent calculation center are generated based on the data analysis result, and the energy efficiency management and control standards comprise a server load threshold value, carbon emission intensity limitation and a cooling system energy efficiency standard; dynamic regulation and control of computing power are implemented based on an energy efficiency management and control standard; and real-time load conditions, energy consumption characteristics and carbon emission intensity of the server are combined. According to the invention, by dynamically generating the energy efficiency management and control standard, feeding back the regulation and control strategy in real time and optimizing the computing power distribution, the efficient distribution of the computing power of the intelligent computing center is realized, the resource utilization rate is improved, and the carbon emission and the energy consumption are obviously reduced.

The invention discloses a container tracking management system and method. The method comprises the following steps: S1, carrying out dynamic encryption binding and multi-dimensional data acquisition on an RFID chip; s2, realizing real-time position data acquisition of the container under different environmental conditions through a multi-source signal fusion and error correction algorithm; s3, various sensor modules are installed inside and outside the container, and data processing is carried out through distributed edge nodes; s4, performing on-chain storage on total data generated in the transportation process through a Hash encryption algorithm, and realizing automatic data verification, state tracking and abnormity alarm in combination with an intelligent contract; s5, carrying out real-time dynamic modeling analysis on the transportation path and resource allocation, and dynamically adjusting the transportation plan by using a distributed scheduling strategy; and S6, integrating the real-time state data, the path optimization model and the transportation scheduling decision, and providing a report for a user. The method has the advantages of high positioning precision, high data security, high transportation efficiency and good real-time performance.

The invention discloses a network security active defense method and system for detecting abnormal network behaviors. The method comprises the following steps: S1, constructing a virtualized isolation network environment through a software defined network technology; s2, deploying intelligent dynamic camouflage nodes in the virtualized isolation environment; s3, acquiring a disguised node attack behavior, and identifying a network abnormal behavior through a deep learning technology; s4, extracting network abnormal behavior features, and identifying potential threats through a deep learning technology; s5, a defense mechanism is automatically triggered, a honeynet is started, and abnormal behaviors and potential threats are isolated; and S6, tracing an attack path, and carrying out source positioning. The network security active defense system comprises a network construction module, a deployment module, an identification module, a honeynet, an isolation module and a tracing module. The disguised nodes are deployed through the deployment module to detect abnormal network behaviors, active defense of network security is realized through the honeynet, the isolation module and the tracing module, and the network security is improved.

The invention discloses a standardized electrical switch cabinet detection method based on the Internet of Things, and relates to the technical field of electrical switch cabinet detection, and the method specifically comprises the following steps: obtaining the core information of all abnormal data generated by all sensors in an electrical switch cabinet in real time, and carrying out the analysis after obtaining, evaluating the priority of each abnormal data in the electrical switch cabinet with the high current leakage phenomenon, and dividing each abnormal data into low-priority abnormal data, medium-priority abnormal data and high-priority abnormal data according to an evaluation result; and according to the division result of each abnormal data, constructing an abnormal data hierarchical sorting mechanism, and respectively adopting different sorting and processing measures for low-priority abnormal data, medium-priority abnormal data and high-priority abnormal data. According to the method, the problem of unreasonable priority processing of the abnormal data in a high-current leakage scene is solved, quick response and accurate detection are realized, and the fault processing efficiency and the system reliability are improved.

The invention provides a self-discovery ad-hoc network control method based on a swan-gap operating system, and relates to the technical field of data processing, and the method comprises the steps: based on the swan-gap operating system, extracting the identification information and communication parameters of equipment from all to-be-networked equipment; carrying out compatibility judgment on the communication protocol version and the maximum support bandwidth between the devices; determining a control relationship between the master device and the slave device; dynamically allocating communication resources to each device by adopting a distributed channel allocation algorithm in combination with task requirements of the devices and network bandwidth information; periodically synchronizing the resource state of each device; when the slave device sends a networking quitting request, the master device updates the networking candidate data and re-determines the networking control relationship after releasing the corresponding communication resources; when the master device exits, the device with the highest priority is selected from the slave devices to automatically take over the control role and complete the reconstruction of the networking control relation; according to the invention, the autonomy and accuracy of networking are improved.

An automatic driving resource arrangement and task unloading method based on model segmentation comprises the steps that in an automatic driving system, each vehicle continuously generates a vehicle-mounted task, and a vehicle task calculation model makes a real-time decision according to collected sensing data; each base station carries out task unloading scheduling on a plurality of vehicles in the coverage range; the MEC server communicates with the base station, and carries out computing resource arrangement and unloading task calculation on the edge side; according to the model segmentation method, a lightweight shallow network is deployed for a vehicle to serve as a vehicle model, and a deep network is deployed for an MEC server to serve as an edge model; adopting a residual network Resnet as a backbone network to realize model segmentation; residual blocks in the Resnet are dynamically segmented by segmentation points; according to resource arrangement and task unloading, collaborative decision-making of resource arrangement and task unloading is modeled as a constraint optimization problem for minimizing long-term task completion time delay, then the constraint optimization problem is decoupled as a resource allocation and task unloading sub-problem, and a double-layer DDPG network is constructed to solve the sub-problem.

The invention relates to the technical field of new energy storage, and discloses a liquid leakage detection and collection method for a galvanic pile of a flow battery energy storage system, which comprises the following steps of: arranging a humidity sensor, a gas sensor, a temperature sensor, a visual sensor and a pressure sensor in a key area of the galvanic pile to form a high-density detection network of multi-source data; sensor data are collected and transmitted to a control center in real time, multi-source data are fused through Kalman filtering, Bayesian estimation and a deep learning model, and feature information of liquid leakage is obtained; and based on feature information of multi-source data fusion, a multi-point interpolation method and three-dimensional space modeling are used to realize positioning of a liquid leakage area. The intelligent grading response and control technical scheme is adopted, and factors such as leakage diffusion and environmental conditions are dynamically analyzed, so that grading self-adaptive response of operations such as isolation, cooling, load shedding and shutdown is realized, and compared with the scheme that only single isolation or shutdown is adopted to cope with a leakage event in the prior art.

The invention discloses a method for preparing a sodium-ion battery hard carbon negative electrode material by modifying industrial waste activated carbon. Industrial waste activated carbon is used as a raw material, a high-molecular polymer is used as a modifier, water or an organic solvent is used as a solvent, and the sodium-ion battery hard carbon negative electrode material is obtained through process treatment of firstly mixing, then carrying out medium-low temperature pretreatment and finally carrying out high-temperature carbonization. The method disclosed by the invention is simple and environment-friendly in process, waste utilization of the waste activated carbon generated in the field of waste gas treatment in the electronic industry, the shoemaking industry or the printing industry can be realized, and the prepared hard carbon has the characteristics of high yield, good electrochemical performance and low cost.

The invention relates to a method and a system for an adaptive elastic expansion strategy of an Android distributed edge container. Monitoring the resource use condition of each Android container in real time; wherein the resource use condition of the Android container is determined; according to the resource use condition of each Android container obtained by the resource monitoring module, a preset calculation resource is dynamically allocated to each preset Android container by applying a preset algorithm; and according to different service flow characteristics and specifications of resources required by services, adjusting preset rearranged available container resources, or calling elastic resources to carry out resource expansion. The resources are flexibly allocated according to actual resource requirements and business load conditions of the Android containers, the problem of unbalanced resource allocation and utilization is solved, container expansion can be quickly and flexibly performed when the business volume is increased, manual intervention is not needed, the response time is shortened, the quick increase requirement of the business for the container resources is met in time, and the business efficiency is improved. And the service continuity is ensured.

The invention provides a dimethyl sulfone extraction device and method, and relates to the technical field of dimethyl sulfone preparation. The dimethyl sulfone extraction device comprises a mixing box, a first feeding hopper and a second feeding hopper; the blocking mechanism comprises sliding columns arranged on the side walls of the two ends of the fixed box in a sliding mode, a sealing plate arranged at the ends, away from the fixed box, of the sliding columns, and a driving assembly arranged in the fixed box and used for driving the two sliding columns to move in the same direction so as to intermittently block discharging ports of the first feeding hopper and the second feeding hopper. The wall scraping mechanism can scrape off part of crystals attached to the surfaces of the stirring blades while the stirring blades rotate. According to the invention, sulfite and methanol can be intermittently put into the mixing box in sequence, so that the sulfite and the methanol are doped together to improve the reaction speed of a solution, and part of crystals which are separated out and attached to the surfaces of the stirring blades can be scraped off while the stirring blades rotate; the solution can react thoroughly, and resource waste caused by the fact that crystals cannot be collected subsequently can be avoided.

The invention provides a network packet processing method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving packet network packets of different QoS (Quality of Service) levels, and sending the packet network packets of a real-time service to a corresponding target network card queue; on the basis of a pre-established linear mapping relationship, locking a universal processor CPU core corresponding to the target network card queue and resources of an operating system thread to process the packet network packet of the real-time service; wherein the linear mapping relationship is a linear mapping relationship among a universal CPU core, an operating system thread and a network card multi-queue, so that the Qos resource conflict problem of real-time services and non-real-time services is solved from the bottommost layer of hardware resources such as a network card and a CPU, and the resource entanglement and resource competition risk of the real-time services and the non-real-time services is solved from the framework level; and in combination with software and hardware, high throughput, low time delay and low jitter of real-time services are better supported.

The invention discloses a fetal heart analysis method, device and equipment and a storage medium. The method comprises the steps that fetal heart data and user basic information uploaded by a user are acquired; the fetal heart data and the basic information of the user are input into a preset fetal heart analysis model, a fetal heart analysis result is obtained, and the preset fetal heart analysis model comprises a position coding module, a bidirectional gating circulation unit, a channel attention mechanism, a multi-scale feature extraction module and a feature fusion module; and distributing the fetal heart data, the basic information of the user and the fetal heart analysis result to doctors of different grades according to the fetal heart analysis result. The fetal heart data and the basic information of the user are input into the preset fetal heart analysis model to obtain the fetal heart analysis result, and the preset fetal heart analysis model comprises the position coding module, the bidirectional gating circulation unit, the channel attention mechanism, the multi-scale feature extraction module and the feature fusion module. According to the invention, the accuracy of fetal heart analysis is improved.

The invention discloses an inspection method, system and device for a fire alarm system, relates to the technical field of fire safety, and solves the technical problems of low inspection efficiency and resource waste caused by the fact that a fixed period polling mode is generally adopted in the prior art, a large amount of redundant communication is generated, and system bandwidth and computing resources are occupied. A to-be-queried queue is constructed based on a state response result; generating an inspection result in an instruction sending mode based on the state type in the queue to be queried; based on the real-time load and the load change trend of the to-be-queried queue, an inspection cycle is generated in a self-adaptive mode, lightweight state response results of all fire-fighting components are rapidly obtained through the variable inspection cycle, then the to-be-queried queue is constructed only for the components with the state changed, and refined detailed state query is carried out. And finally, the next inspection period is dynamically and adaptively generated according to the load condition of the queue, so that the generation of redundant data is eradicated from a communication mechanism, and the problems of low inspection efficiency and resource waste are solved.

The present invention is applicable to the technical field of farmland pollutant treatment, and provides a green management and supervision system based on big data analysis technology, including a benchmark data acquisition module for selecting a standard farmland area and performing a complete soil pollution test on it to obtain pollutant benchmark data; a pollutant retention coefficient calculation module for measuring the inflow and outflow of the standard farmland area and other non-standard farmland areas to be treated, and combining water quality testing to calculate the pollutant retention coefficient of the standard farmland area and the non-standard farmland area. The present invention obtains accurate pollutant benchmark data by selecting a standard farmland area for comprehensive soil pollution testing, and scientifically calculates the pollutant retention coefficient of the farmland by combining the inflow, outflow and water quality testing.

The invention discloses a take-out delivery service range division method, device and equipment and a storage medium. The method comprises the following steps: dynamically calculating delivery time through store position information, a dynamic traffic factor, a dynamic meal delivery factor, a rider type factor, an optimization factor and an end point delivery difficulty factor; calculating the shortest passing time from the store to each node in the road network according to the delivery time, and generating a special delivery isochrone and a fast delivery isochrone according to the shortest passing time; according to a preset transport capacity density threshold value and a preset historical punctuality rate threshold value, carrying out dynamic optimization on the dedicated delivery isochrone, and according to an optimization result and the fast delivery isochrone, generating a fast delivery service area, the problems that a traditional take-out delivery range division method depends on a static distance and cannot adapt to resource waste and service blind areas caused by transport capacity distribution, weather changes and order density fluctuation in real time are effectively solved, accurate dynamic adjustment of the delivery service range can be achieved, and the delivery punctuality rate, the resource utilization rate and the user order placing experience are remarkably improved.

The invention discloses an intention-driven task transmission path selection method and intention-driven task transmission path selection equipment in an uncertain environment, and the intention-driven task transmission path selection method in the uncertain environment comprises the following steps: when a source node has a task unloading demand, sending a message containing task data to a destination node, according to the message containing the task data, task transmission path selection is achieved through a task transmission path selection model, and an optimal task transmission path is obtained. The invention discloses an intention-driven task transmission path selection method and intention-driven task transmission path selection equipment in an uncertain environment. A task transmission and execution algorithm with deterministic task processing time delay constraint in an uncertain environment can solve the problem of task processing in an emergency, a scene can be modeled into a pervasive edge computing environment composed of a plurality of heterogeneous devices, and the devices can be mutually connected through wireless communication.

The present invention discloses a robot integrated scheduling system integrating multiple brands, and relates to the technical field of robot integrated scheduling, comprising a task acquisition module, which is used for a scheduling system to obtain a list of tasks to be executed from a production management system; a robot division module, which is used to generate a plurality of groups of task switching time interval vectors; a task allocation module, which is used to allocate tasks to robots based on a plurality of groups of task switching time interval vectors and a task list; a data acquisition module, which is used to obtain multi-robot efficiency data and system resource data when robots perform tasks; a task switching time interval evaluation model is constructed based on machine learning; and a screening module, which is used to perform data analysis to obtain screened task switching time interval vectors, which are applied to the integrated scheduling of robots of multiple brands, and solve the problem that the setting of task switching time intervals in multi-brand robot systems lacks flexibility, and easily leads to an imbalance between resource utilization and task connection efficiency in the scheduling system.

An intelligent tool car relates to the technical field of tool cars. According to the intelligent tool car provided by the utility model, paper drawings are replaced by electronic drawings by combining existing hardware modules. Therefore, automatic updating of online drawings is realized, resource waste is reduced, and drawing retrieval and updating efficiency is improved. Furthermore, the tool is intelligently associated with the drawing, so that the operation error and the tool loss rate are reduced, and the anti-loss management of the tool can be realized. Furthermore, through the modular design and the plug-and-play characteristic of existing hardware, the manufacturing cost of the equipment is reduced by 30%, development programs do not need to be customized, the equipment can be directly adapted to management systems of different workshops, and the popularization threshold is low. The system is suitable for non-standard processing scenes such as digital intelligent plate cabinet workshops and the like, and is used for solving the problems of lagging drawing management, low tool use efficiency, resource waste and the like.

The invention discloses a self-compacting concrete of carbonization synergistic modified solid waste aggregate and admixture and a preparation method thereof, wherein the preparation method comprises the following steps: 1) 40-60 parts of admixture, 100-150 parts of aggregate, and 50-70 parts of water are placed in a vertical stirred mill, industrial tail gas is introduced at a rate of 10-30L / min, and grinding is performed at a speed of 400-700r / min for 30-40min to obtain a mixed material containing aggregate and admixture; 2) the mixed material is stirred for 3-5min with 100 parts of PO42.5 cement, 250-300 parts of crushed stone, and 0.4-0.7 parts of water reducer to obtain self-compacting concrete. In the present invention, under the action of carbon dioxide, the admixture and aggregate are wet-milled and modified, and the stability of the modified aggregate is qualified, and the self-compacting concrete prepared by the modified admixture and aggregate mixture has high strength, excellent slump expansion and anti-segregation performance.

The invention provides a new energy system operation state monitoring analysis method and device based on a multi-level structure and a storage medium, and relates to the technical field of data monitoring analysis. The method comprises the following steps: dividing acquired data of a new energy monitoring system according to a preset hierarchical structure to obtain hierarchical structure data; constructing the hierarchical structure into a hierarchical data model through a dynamic time sequence modeling algorithm; constructing a cross-regional panoramic monitoring graph, and performing optimization scheduling of regional hierarchical data in combination with a dynamic network optimization algorithm; and collecting real-time data of the new energy access point through an incremental data synchronization algorithm, performing data analysis on the new energy access point, and generating an analysis result. By introducing hierarchical data modeling, dynamic data synchronization, incremental data processing and panoramic modeling, the data management flexibility, the real-time monitoring precision, the cross-regional data synchronization and scheduling efficiency and the risk assessment and abnormal response capability of the new energy monitoring system are remarkably improved.

The utility model provides a printing roller maintenance device for printing equipment, which belongs to the technical field of printing roller maintenance and comprises two fixing frames arranged in parallel, a printing roller body is rotatably connected between the two fixing frames, a first motor is fixedly connected to the outer side wall of one fixing frame, and a second motor is fixedly connected to the outer side wall of the other fixing frame. The driving end of the first motor is fixedly connected with one end of the printing roller body, the top ends of the two fixing frames are detachably connected with a top frame through bolt assemblies, and the upper end face of the top frame is symmetrically and fixedly connected with two telescopic cylinders. By means of the reciprocating lead screw, the moving seat, the guide rod, the water tank, the sponge and the water adding pipe, the printing roller is cleaned through the wet sponge, the phenomenon of water stain splashing is avoided, waste of water resources can be avoided while the printing roller is well cleaned, and the printing roller cleaning device is suitable for popularization and application. The problems that water is prone to splashing and water resources are wasted during cleaning and maintenance in the prior art are solved.

This invention discloses a method for the biological drying of sludge, comprising the following steps: baking biomass materials, mixing the resulting baked product with sludge, biochar materials, and a conditioner for biological drying, thereby completing the sludge drying process. In this invention, by biologically drying the mixture of baked product, sludge, biochar materials, and conditioner, not only can the self-generated heat within the system be used to effectively dewater the sludge in a very short time, but the bioavailability of the microbial carbon source can also be improved, effectively reducing the generation of polluting gases. This method can effectively reduce the emission of polluting gases while achieving rapid dewatering. It has advantages such as simple process, low treatment cost, low energy consumption, high drying efficiency, good dewatering effect, low polluting gas production, and low content of toxic and harmful components in the dried product. It can solve the problems of biomass resource waste and pollution, achieve sludge reduction and resource utilization, and has high returns and good application prospects.

The utility model provides a winding device. The winding device is used for winding materials and comprises a mounting structure and a winding structure, the winding structure is rotatably arranged on the mounting structure and connected with one end of the material, and the winding structure drives the material to rotate around the rotating axis of the material so that at least part of the material can be wound on the winding structure; the adjusting structure is arranged on the mounting structure and located on the peripheral side of the winding structure, the adjusting structure comprises an adjusting part, and the adjusting part is movably arranged and connected with at least part of materials which are not wound on the winding structure; wherein in the rotating process of the winding structure, the adjusting part drives the part of materials to move so as to adjust the winding position of the part of materials on the winding structure. The waste edge collecting device effectively solves the problem that in the prior art, space resources and manpower resources are wasted in the mode of collecting electronic cloth processing waste edges.

The invention discloses a camera data correction method and device and a nonvolatile storage medium. The method comprises the steps that application demand data corresponding to a target camera are acquired, a demand feature set is determined according to the application demand data, and the application demand data comprise a service type and a correction target corresponding to the target camera; determining a demand type vector according to the demand feature set, a preset distortion type and a keyword corresponding to the preset distortion type; determining a distortion correction algorithm matched with the demand type vector, and correcting image data collected by the target camera by using the distortion correction algorithm; and carrying out distortion detection on the corrected image data so as to determine a correction quality index of the image data, and outputting the corrected image data under the condition that the correction quality index is determined to be not less than a preset index threshold value. The technical problems of high resource consumption and low efficiency caused by a complex correction method are solved.

The application discloses a kind of based on multiple-source solid waste's improved red sandstone roadbed filler and mix proportion optimization method, belong to the field of red sandstone filler green low carbon improvement.Improved red sandstone roadbed filler is red sandstone as improved matrix, with match calcium carbide slag, rice husk ash, fly ash as cementing component preparation, wherein calcium carbide slag provides calcium source and alkaline environment, rice husk ash provides silicon source, fly ash provides aluminum source, three reactions occur in alkaline environment and generate abundant cementing products, realize red sandstone improvement.At the same time, with three cementing component contents as design variable, with bearing ratio, unconfined compressive strength, water stability coefficient as road evaluation index, construct road performance response model, through multi-index optimization, clear cementing component optimization ratio range.The method can exert the synergistic effect of multiple-source solid waste chemical composition, can be optimized according to different application scene performance requirements Ratio, realize red sandstone efficient improvement and multiple-source solid waste high-value utilization, with economic benefit and environmental benefit.

The present invention provides a cable sheath steel rope braided rigging, comprising a cable sheath body formed by braiding a plurality of steel wire ropes, the cable sheath body comprising a plurality of detachably connected cable sub-sheaths; the cable sub-sheath comprising a first connecting piece arranged on a first end of the cable sub-sheath, and a second connecting piece arranged on a second end of the cable sub-sheath; the first connecting piece and the second connecting piece are detachably connected, the first connecting piece of the cable sub-sheath is connected to the second connecting piece of the cable sheath adjacent thereto; the first connecting piece and the second connecting piece each comprise a plurality of first sliding pieces arranged inside themselves, the first sliding piece is connected to a first end or a second end of the steel wire rope in a one-to-one correspondence, and the sliding direction of the first sliding piece is the circumferential direction of the cable sub-sheath; the side surface of the cable sub-sheath is detachably connected, and is used for removing the steel rope wrapped by the cable sub-sheath from the side surface of the cable sub-sheath.

The application discloses a method and a server for generating ancient poetry video based on voice interaction video model, and relates to the technical field of artificial intelligence education, comprising: receiving a user's ancient poetry learning voice instruction and converting it into an instruction text; obtaining context information of the current user conversation; identifying whether the current intention is to generate an ancient poetry video according to the recognized instruction text and context information; when the intention is to generate an ancient poetry video, searching for corresponding author and original text information according to the recognized ancient poetry title; generating an ancient poetry meaning interpretation text by receiving the ancient poetry title, author and original text information through a text generation large model; and generating a video depicting the expression of ancient text or poetry by receiving the ancient poetry title, author, original text information and the ancient poetry meaning interpretation text through a preset video generation large model in real time. The application aims to solve the problem that users cannot generate ancient poetry learning videos in real time through voice interaction in the prior art.

The application discloses a data processing device for LDPC code layered decoding, which comprises a configurable computing unit capable of switching between row update mode and column update mode, a storage system physically divided into multiple independent storage banks, an address generation unit and a control unit. The address generation unit is configured to map access addresses of parallel data requests to different independent storage banks, and the control unit is configured to schedule column update tasks to be performed first and then closely related row update tasks in a decoding layer, wherein the row update tasks directly read the latest variable node messages generated by the column update tasks. The application guarantees the immediate reuse requirement of the layered decoding algorithm for the latest messages by constructing a high-bandwidth parallel data access path, eliminates the memory access bottleneck, and thus can fully exert the performance advantage of the layered decoding algorithm to realize high-throughput decoding processing.

The invention belongs to the technical field of solid waste recycling. The invention discloses a method for realizing high-value recycling of secondary aluminum ash and synchronous deep defluorination and dechlorination by utilizing hydrothermal synthesis. The method comprises the following steps: firstly, pretreating secondary aluminum ash, then preparing the pretreated secondary aluminum ash and water into slurry, and adding a specific defluorinating agent and a dechlorinating agent into the slurry to construct a synchronous reaction system; the system is subjected to hydrothermal reaction under high-temperature and high-pressure conditions, so that fluorine and chlorine elements are respectively fixed and converted into stable compounds. Solid-liquid separation is carried out after the reaction is completed, an obtained solid product can be used as a raw material for preparing a zeolite molecular sieve or an aluminum-based material, and salt is recovered from a liquid part through evaporative crystallization. According to the method, deep removal of harmful elements and a high-value recycling process of beneficial components are coupled to a single hydrothermal system, and efficient harmless and high-value recycling utilization of the secondary aluminum ash is achieved.