606 results about "Data Adjustments" patented technology

The invention discloses a real-time behavior monitoring and dynamic optimization system for an advertisement putting strategy, and relates to the technical field of advertisement putting and user behavior analysis. A real-time multi-source user behavior data acquisition module acquires data; the distributed storage and indexing module supports fragmented storage, capacity expansion and multi-dimensional indexing; the behavior feature extraction and analysis module extracts features and identifies a time sequence rule; the putting effect evaluation module compares data through an index system and positions an effect short board; the user portrait dynamic updating module adjusts the label weight according to the latest data; the strategy optimization decision module optimizes parameters in combination with the portrait and the evaluation result; the execution scheduling module issues an instruction and monitors a state; the historical data mining and model training module is used for mining rules and iteratively training the model; and the visual interaction configuration module provides an interface and supports parameter configuration and data, effect and optimization suggestion display. According to the invention, full-scene real-time monitoring and cross-platform identity association of user behaviors are realized, and support is provided for refined advertisement marketing.

The invention discloses an integrated water quality monitoring and processing system for aquaculture, and the system comprises a data collection module which is used for obtaining dissolved oxygen, ammonia nitrogen, pH value, temperature and flow data from a plurality of spatial distributed sensing nodes; the data preprocessing module is used for completing noise removal, correction and time sequence synchronization; the water quality state estimation module is used for outputting real-time multi-point water quality states based on a distributed unscented Kalman filtering algorithm; the space-time fluid modeling module is used for constructing a Lagrange model to extract a flow velocity field and a diffusion coefficient; the scheduling optimization module is used for generating an aeration and dosing scheme by adopting an improved multi-target Pareto optimization algorithm based on a space-time sensitive boundary; the execution module is used for controlling an air blower, an aeration pipe and a dosing pump to complete oxygenation and dosing operations; and the self-adaptive updating module is used for collecting feedback data to adjust filtering gain and optimizing parameters so as to realize closed-loop control of the system.

The invention relates to the technical field of ship control, in particular to a fishing boat control system based on data analysis, which comprises a traction load analysis module, a fluctuation condition division module, an attitude disturbance estimation module, a propulsion power regulation module and a rudder angle correction output module. According to the method, by analyzing the traction force load sequence value and the moment arm length of the fishing net traction point, calculating the left and right side offset torque and marking the action direction, the attitude adjustment precision of the ship is optimized, the operation sea condition level is adjusted according to data, and the ship can be subjected to more reasonable attitude estimation and adjustment under the dynamic working condition; the wind pressure change rate and the pitch angle rate are combined to judge the direction resultant force trend, and the navigation attitude is adjusted according to the sea condition grade, so that the ship can more accurately resist the influence of sea surface storm waves and maintain the course stability, and the rudder angle is corrected by adjusting the propulsion power in real time, limiting the adjustment amplitude of the propulsion power and correcting the rudder angle according to the real-time data of the navigation attitude. And the propulsive efficiency and the navigation precision are optimized.

The invention relates to the technical field of artificial intelligence, and discloses a professional knowledge question and answer intelligent customer service system based on a self-optimization mechanism. The system comprises a user intention analysis module, a knowledge processing module, a self-optimization learning module and an interactive presentation module. A semantic understanding unit of the user intention analysis module generates a user intention signal; after the knowledge processing module receives the signal, a knowledge retrieval unit outputs related knowledge fragments and confidence, an answer generation unit forms candidate answers, and a quality evaluation unit determines an optimal answer according to the confidence; in the self-optimization learning module, a feedback analysis unit adjusts answer generation parameters according to user interaction data, a strategy adjustment unit optimizes a retrieval strategy in combination with an optimal answer and a historical dialogue, and a knowledge updating unit updates a knowledge base depending on an external knowledge source; and a multi-round dialogue management unit of the interactive presentation module adjusts a dialogue process, and a visual presentation unit outputs a natural language text and collects user feedback to a feedback analysis unit.

The invention relates to the technical field of mine equipment monitoring and maintenance, and discloses a mine equipment state monitoring and maintenance method based on the Internet of Things, which comprises the following steps: S1, multi-source data acquisition: synchronously acquiring equipment operation parameters and environmental parameters through vibration, temperature and pressure sensors and environmental sensors deployed on mine equipment; s2, edge calculation processing: performing filtering and anomaly detection on the sensor data at a mine edge gateway to generate a compressed data packet; s3, online learning and model dynamic updating; s4, new equipment is accessed; s5, maintenance decision and resource scheduling; and S6, performing closed-loop feedback optimization. High-error historical sub-trees are dynamically eliminated, new sub-trees are generated, model parameters are adjusted in combination with maintenance feedback data, on the basis that historical effective knowledge is reserved, equipment dynamic features are extracted, accurate matching of prediction results and maintenance strategies is ensured, and the self-learning ability and maintenance decision reliability of the model are remarkably improved.

The invention provides a spatio-temporal data fusion-based power distribution network load prediction method and system, and relates to the technical field of power distribution network load prediction, and the method comprises the steps: collecting related data of a power distribution network, carrying out the wavelet transform decomposition of historical load data, obtaining a load feature matrix, constructing a hierarchical graph convolution network based on topological structure data, and extracting topological correlation features; and generating a spatial-temporal feature tensor through tensor decomposition fusion, training a depth probability prediction model adopting a variational auto-encoder structure, and adjusting prediction probability distribution in combination with environmental data. According to the method, the prediction precision is improved, a complex space-time dependency relationship can be captured, and reliable uncertainty quantization is provided.

The present application relates to a BIM-based hanging basket design method, computer device and computer-readable storage medium, wherein the design method comprises following steps: a parameter acquisition step; a hanging basket modularization step: decomposing structures of hanging baskets into a plurality of design modules; a selection step; a calculation step: calculating parameters of the design modules using a structural mechanics calculation method and / or a finite element calculation method; preliminary BIM model building step: building models of the design modules and a preliminary BIM model of the hanging basket; an optimization iteration step: converting the preliminary BIM model of the hanging basket into a finite element model for calculation, and feeding calculation results back to the preliminary BIM model for structural adjustment, repeatedly performing iterative calculations to obtain optimized hanging basket parameter data; final BIM model acquisition step: the BIM model of the hanging basket adjusted according to the optimized hanging basket parameter data is a final BIM model of the hanging basket. The design method enables autonomous calculation and design of the hanging basket with good versatility.

The invention discloses a power data security transmission strategy dynamic optimization method based on gray measurement, which comprises the following steps: S1, collecting and preprocessing multi-source heterogeneous data in a power system, and generating a time sequence data set and a structure attribute data set; s2, performing privacy protection and noise addition on the time sequence data set and the structure attribute data set by applying a differential privacy mechanism; s3, performing evaluation by adopting a gray scale measurement and calculation method, calculating a gray scale weight and generating a transmission strategy; s4, according to the gray scale weight classification data, adjusting a transmission path and a time sequence; s5, dynamically adjusting the differential privacy noise intensity and the gray scale weight according to the network bandwidth, the transmission delay and the data requirement; and S6, continuously monitoring the transmission efficiency and the privacy effect, and adjusting a transmission strategy and a protection mechanism in real time according to feedback. According to the method, the dynamic collaborative optimization of privacy protection and scheduling efficiency of the power data in the transmission process is realized by fusing a differential privacy mechanism and a gray calculation method.

A method may include obtaining, from a camera device, thermal image data for a steam area of a plant facility. The steam area may include a steam trap for a steam network. The method may further include obtaining plant steam data regarding the steam trap. The method may further include determining pixel data regarding the steam trap using the thermal image data and an image segmentation process. The method further includes determining various temperature values across the steam trap using the pixel data. The method may further include determining predicted steam trap data using the temperature values, the plant steam data, and a machine-learning model. The method may further include transmitting a command that adjusts one or more parameters of the steam network based on the predicted steam trap data.

The invention belongs to the technical field of robot navigation and path planning, and particularly discloses and provides a dynamic navigation planning method and system for a service robot, which overcomes the limitation of single-dimensional analysis in a complex dynamic scene by constructing a dynamic social thermodynamic diagram and deducing group dynamic intention data. The perception precision of the environment structure and the people stream situation is improved; a linkage mechanism among a dynamic social thermodynamic diagram, individual behavior characteristics and path planning is established, and a social cost function is generated to optimize a navigation path according to the traffic efficiency and social etiquette of group future dynamic vectorization evaluation; the actual influence of the navigation behavior of the robot on the environment is monitored in real time, and a planning strategy is adjusted in combination with feedback data, so that the adaptability of the navigation decision and the continuous improvement of the environment acceptance degree are realized.

A system for vendor deduplication. The system creates embeddings of entity names and creates an initial entity graph comprising entities whose embeddings are related. The initial entity graph includes nodes representing the entity names linked together by edge weights indicating their similarity. The system adjusts the edge weights between the entity names according to transactional data related to the entities to create a final entity graph and merges the entity names as a common entity based on the adjusted edge weights in the final entity graph.

The invention relates to the technical field of road engineering detection, in particular to a road disease recognition method and system based on electromagnetic waves and photographic imaging, and the method comprises the steps: firstly obtaining electromagnetic wave detection data and photographic imaging data of a road region, then synchronously detecting the distribution position and thickness of a road thin water film, generating a rasterized water film feature map, and finally obtaining a road disease recognition result. Then, according to the water film characteristic pattern, dynamically correcting bimodal data interference, adjusting a reflected wave amplitude value and a time domain delay parameter for electromagnetic wave detection data, compensating a gray difference and an edge gradient value for photographic imaging data by applying a local reflection suppression algorithm, and finally, fusing the corrected data and associating the state of the water film characteristic pattern to eliminate coupling misjudgment. The system comprises a data acquisition unit, a water film detection unit, a double-domain correction unit and a fusion decision unit, the problem of insufficient identification precision caused by a thin water film is solved, the road disease identification precision is improved, and a reliable basis is provided for road maintenance.

An apparatus including a policy acquisition circuit structured to interpret a vehicle policy data value including vehicle status data; a policy processing circuit structured to generate parsed policy data that includes a vehicle data collection description; a policy execution circuit structured to collect vehicle data from one or more end points of at least one network zone of a vehicle; a vehicle data transmission circuit structured to transmit at least a portion of the collected vehicle data; and a vehicle status data adjustment circuit structured to interpret a vehicle status data collection change value.

The invention relates to the technical field of production safety and intelligent monitoring, in particular to a cosmetic production line safety monitoring method and system based on data analysis, and the method comprises the steps: obtaining real-time operation parameters through a multi-source data collection module, and generating a production environment dynamic mapping graph; extracting a fluctuation trend and abnormal distribution characteristics, and generating a region data adjustment instruction set; adjusting a signal acquisition strategy, and constructing a regional signal alignment state table; identifying the signal intensity variation, and forming a regional signal adjustment mark graph; and finally outputting a monitoring area state evaluation value list. According to the method, the signal fluctuation expression precision and the dynamic regulation and control capability can be remarkably improved, the adaptability and the response sensitivity of safety monitoring in a complex production environment are enhanced, and high-precision local compensation and equipment state quantitative judgment are realized.

The invention relates to the technical field of power plant equipment maintenance, in particular to an industrial internet power plant equipment predictive maintenance system based on digital twinning. The system comprises an equipment data acquisition unit, a digital twinning construction unit, a state prediction unit, a maintenance strategy generation unit and a dynamic adjustment unit. The equipment data acquisition unit acquires multi-equipment real-time operation data, and a multi-dimensional data set is formed through time alignment and space registration; the digital twin construction unit performs sparse reconstruction on the data set to obtain target data and abnormal indication data; the state prediction unit generates a health state prediction result containing the remaining service life and the fault occurrence probability in combination with the target data, the historical maintenance records and the operation parameters; a maintenance strategy generation unit generates a scheme containing a maintenance priority and a time window; the dynamic adjustment unit adjusts the scheme according to the abnormal indication data. The system realizes comprehensive monitoring, accurate prediction and dynamic maintenance of equipment.

The invention discloses a medical record data mining and potential risk prediction method and system based on deep learning, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a first semantic vector set containing the current symptom multi-role chief complaint information of a target child, multi-modal physiological data, basic treatment information and initial cognitive level model parameters, a conflict vector set is generated through conflict recognition, initial cognitive level model parameters are adjusted in combination with multi-modal physiological data, individual cognitive level model parameters are obtained, and then a questioning text set is generated according to the conflict vector set and the individual cognitive level model parameters; after feedback is received, conflict resolution is carried out on the first semantic vector set to obtain a second semantic vector set, the second semantic vector set is fused with basic doctor seeing information to generate medical record combination feature data, and a potential disease risk prediction result of the target child is generated according to the medical record combination feature data; the method has the beneficial effects that the multi-role chief complaint information conflict in the child medical record can be effectively processed, and the potential disease risk prediction accuracy is improved.

The invention discloses a naval vessel formation-oriented MADDPG super-network parameter optimization method based on differential evolution, and the method comprises the steps: constructing a naval vessel formation cooperative combat environment, setting a naval vessel as an intelligent agent, and setting task information for the intelligent agent; loading task information, and generating an initial strategy; according to the initial strategy, the intelligent agent interacts with the environment and collects data; training super-network parameters of the MADDPG model according to the data, and optimizing the super-network parameters by adopting a differential evolution algorithm to obtain an optimal parameter combination; loading the optimal parameter combination into the MADDPG model, and evaluating the performance of the intelligent agent to obtain an evaluation result; and the initial strategy is optimized according to the evaluation result, the intelligent agent interacts with the environment again, new data is collected, the super-network parameters are adjusted according to the new data, and the super-network parameters are iteratively optimized until a final training model is obtained. According to the method, coevolution optimization of the multi-agent strategy network is realized, and the convergence speed and stability of the strategy network are improved.

The invention discloses a traditional Chinese medicine grinding control system, which relates to the technical field of traditional Chinese medicine grinding control and comprises a medicinal material characteristic sensing module, an intelligent calculation analysis module, a dynamic execution adjustment module, a multi-mode optimization control module and a system coordination updating module. The medicinal material characteristic sensing module collects physical and texture characteristic data of medicinal materials; the intelligent calculation and analysis module fuses the medicinal material processing knowledge base and historical grinding process data to generate initial grinding control parameters; the dynamic execution adjustment module adjusts the operation parameters of the grinding mechanism in combination with the real-time grinding state data; the multi-modal optimization control module monitors the deviation between actual quality parameters and target quality parameters of powder, and a self-adaptive decision algorithm is used for optimizing regulation and control parameters of a grinding area; the system coordination updating module collects whole-process data and performance index evaluation and generates a system optimization instruction, and the instruction corresponding module adjusts the rotating speed and pressure parameters of a grinding area of the vertical grinding machine. According to the system, intelligent and precise control over medicinal material grinding is achieved, and the stability and consistency of the grinding quality are improved.

The invention relates to the technical field of intelligent operation and maintenance data, and discloses a data acquisition method based on big data of an intelligent operation and maintenance platform. The method comprises the following steps: setting a data monitoring range based on a platform network topology structure, and obtaining the type, data volume and updating frequency of a data source in the range; predicting a data flow trajectory through a data characteristic analysis model, calculating a data intrusion coefficient in combination with a monitoring range and a preset data safety area, calculating a data risk coefficient according to data source information, and summing the data intrusion coefficient and the data risk coefficient to obtain an acquisition demand index; setting a preset threshold value, and judging whether to adjust the acquisition parameters or not according to a comparison result; if so, generating an acquisition path based on a data source position, acquiring a data adjustment track after acquisition, and judging whether to start a data interference mechanism or not according to the overlapping amount of the data adjustment track and the safety area. The method can dynamically adjust acquisition parameters, quantitatively evaluate acquisition requirements and guarantee data security.

The invention provides an interactive control system and method for a power module and an overcharge pile, a storage medium and a computer program product, and the method comprises the steps: obtaining a charging control parameter according to the input time sequence state data of a battery through a charging control parameter prediction model based on deep learning; generating a power instruction according to the charging control parameter and sending the power instruction to the power module; after the power supply module executes the power instruction, an instruction execution result and battery state data are transmitted back to the overcharge pile main control software; and the overcharge pile main control software adjusts the weight of the charging control parameter prediction model according to the received data or regenerates a power instruction based on the latest battery time sequence state data. According to the invention, the charging time can be shortened, the risks of overheating, overcharging and the like can be prevented, different battery states and complex working conditions can be adapted, and the real-time requirement of an overcharging scene on a control instruction and state data can be met.

The invention discloses an intelligent management and control system and method for energy and carbon emission of a container wharf, and relates to the technical field of container management and control, and the method comprises the steps: configuring a sensor interface, collecting the multi-source energy consumption data of a wharf operation site, carrying out the time-space segmentation processing of the collected data based on a preset time window, and generating a segmented energy consumption data set; the data analysis module is used for calculating an energy consumption coupling coefficient among different operation links by adopting a user-defined multi-dimensional dynamic correlation model based on the segmented energy consumption data set; constructing a rule base based on historical energy consumption fluctuation characteristics and a multi-dimensional coupling coefficient variation trend, and automatically generating an abnormal early warning signal by adopting nonlinear logic inference; outputting a regulation and control instruction according to the early warning signal, dynamically adjusting operation parameters of the energy consumption unit, and periodically backtracking historical data to adjust parameters of the association model; a wharf three-dimensional digital environment is constructed, energy consumption and carbon emission indexes are mapped in real time, and three-dimensional dynamic display of abnormal early warning and regulation feedback is achieved.

The invention discloses a financial risk early warning method, and relates to the technical field of financial management, and a risk early warning system adopted by the method comprises a financial data acquisition module, an analysis sensitivity adjustment module and an auxiliary risk identification module. The financial data acquisition module is used for performing data acquisition on financial data change of a fund circulation path and distributed fund flow time points, and the analysis sensitivity adjustment module is used for adjusting the financial analysis frequency of the risk analysis unit according to the acquired data. The auxiliary risk identification module is used for detecting the head end of a financial risk signal by adopting a manual processing method when the risk analysis unit fails to accurately identify the front point of the risk signal; and the financial data acquisition module comprises a fund access recording module, a financial data change acquisition module, a distributed detection unit, a financial structure mapping module and a financial risk analysis unit. The system has the characteristic of automatic risk response.

The invention discloses a vision and laser collaborative assembly positioning method and system, and belongs to the technical field of industrial automation control, and the method comprises the steps: obtaining stereo image data and positioning light spot data, generating multi-source input data, and carrying out the analysis and matching, calculating initial pose estimation, and carrying out the positioning of the three-dimensional image data and the positioning light spot data. Generating a visual positioning result, comparing the visual positioning result with theoretical position data, correcting deviation, generating cooperative positioning data, combining a standard operation process file, generating a visual guiding scheme containing a display instruction and a laser control instruction, synchronously executing the display instruction and the laser control instruction, realizing assembly guiding, and performing assembly. And meanwhile, the assembly process is monitored in real time to generate operation progress data, and the detailed degree of the visual guide scheme is adjusted in combination with historical operation data. According to the method, dynamic compensation and cooperative positioning are carried out by acquiring the three-dimensional image and the laser spot data, and a virtual-real combined guiding scheme is adjusted in real time, so that high-stability self-adaptive assembly process control can be realized.

The invention provides a cooling system, a control method of the cooling system and a data center, and relates to the technical field of server heat dissipation. The cooling system comprises at least one liquid cooling subsystem and at least one air cooling subsystem, the liquid cooling subsystem is connected with a first interface end of the cold source system looped network, the air cooling subsystem is connected with a second interface end of the cold source system looped network, a third interface end of the cold source system looped network is connected with the cold source system, the first interface end is provided with a first electric valve, and the second interface end is provided with a second electric valve. The first interface end is provided with a first electrically operated valve, the second interface end is provided with a second electrically operated valve, the first electrically operated valve is configured to obtain current flow data of the liquid cooling subsystem and adjust the opening degree of the first interface end according to the current flow data of the liquid cooling subsystem, and the second electrically operated valve is configured to obtain current flow data of the air cooling subsystem and adjust the opening degree of the first interface end according to the current flow data of the air cooling subsystem. And the opening degree of the second interface end is adjusted according to the current flow data of the air cooling subsystem. The problems that an existing cooling system is complex in structure, high in water resource consumption and poor in control precision are solved.

The invention discloses a satellite data storage safety monitoring method, system and device and a medium, and belongs to the technical field of safety monitoring, and the method comprises the steps: collecting satellite data, preprocessing the satellite data, generating a chaotic mapping initial seed according to the preprocessed satellite data, and storing the chaotic mapping initial seed in a database; setting a mapping parameter based on the chaotic mapping initial seed and generating a key, and encrypting an access path by using the key; storing the satellite data and the encrypted access path to a database, calculating a stability index based on the encrypted access path, and performing abnormality judgment according to the stability index; feedback data in the safety monitoring process are collected, the mapping parameters are adjusted based on the feedback data, and the adjusted safety monitoring result is displayed through a visual interface. According to the method, the security of data encryption is improved, the capability of detecting and responding to abnormal behaviors in the storage process is enhanced, and the anti-cracking capability of the encryption method is improved.

The invention provides an anti-backflow system, and the system comprises a storage and charging integrated cabin which is used for storing electric energy; the storage and charging integrated cabin comprises a charging pile, an energy storage module, an intermediate relay and a switch which are electrically connected; the control module is configured to obtain static data and dynamic data; determining the output power of the energy storage module and the charging pile based on the static data and the dynamic data; acquiring power supply data; and based on the power supply data, adjusting the power supply condition among the energy storage module, the charging pile and the commercial power, and determining the opening or closing of a first switch node, a second switch node, a third switch node, a fourth switch node, a fifth switch node and an anti-countercurrent contactor, so as to solve the problems that the utilization rate of distributed energy is greatly reduced due to a current anti-countercurrent control scheme; and equipment loss is accelerated, the service life of equipment is shortened, and the operation and maintenance cost is increased.

The invention discloses an out-of-band management method and device based on a solid state disk, and relates to the technical field of solid state disks, and the out-of-band management method comprises the steps: obtaining an original signal from a system management bus channel or a PCIe expansion channel in a solid state disk system; determining an original command corresponding to the original signal; analyzing the original command into a target command, and executing the function of the solid state disk system based on the command type of the target command to obtain an execution result; according to the execution result, a response message adapted to the system management bus channel or the PCIe extension channel is generated, and the response message comprises operation data of the solid state disk; and adjusting the priority of the target command by using the operation data, and through the technical scheme disclosed by the invention, the problems of low efficiency and poor flexibility of out-of-band management in related technologies are solved, and the out-of-band management efficiency and flexibility of the solid state disk are improved.

The invention relates to the field of communication, and discloses an intelligent traffic scheduling optimization method, device and equipment and a storage medium, and the method is used for 5G network intelligent traffic scheduling optimization. The method comprises the following steps: receiving a service request, analyzing the service request to obtain a 5G standard service type, an application scene and a 5G network slice identifier, then obtaining an SLA parameter corresponding to the service request and a candidate link required by service transmission, and converting the SLA parameter into an SLA preference vector; acquiring global data of the candidate link, and predicting by using the network state prediction model to obtain a predicted network state of the candidate link; the SLA preference vector is used as optimization target guidance, the predicted network state is used as a constraint condition, and a global optimization routing strategy is calculated through a multi-target optimization algorithm; and generating a control message packet based on the global optimization routing strategy, issuing the control message packet to the network forwarding equipment, and adjusting parameters of the network state prediction model and the multi-objective optimization algorithm based on the actual performance data after execution.

The invention discloses a method for detecting and analyzing the defect or damage condition of a full-water pipeline, and the method comprises the steps: presetting a sound wave reflection time threshold value of each medium interface when an underwater robot is located in the middle of the pipeline according to the size of the full-water pipeline, and carrying out the sound wave detection through the underwater robot, the collected reflection sound intensity and reflection time data are transmitted to the data processing module, the data processing module carries out pre-classification, whether the collected reflection time is compared with a sound wave reflection time threshold value or not is judged according to the classification condition, a medium algorithm is matched, and the medium algorithm obtains the distance of the reflection time and the reflection sound intensity; and judging whether the reflection interface accords with a medium interface corresponding to the medium algorithm, if so, uploading and adjusting the underwater robot to keep the middle position according to the distance data, if not, uploading and reporting an error, and finally, receiving data three-dimensional modeling by a modeling analysis module, and generating a three-dimensional detection diagram. The problem that the identification effect of the deformation or damage condition of the pipeline covered by the sediment is poor is solved.

A semiconductor memory apparatus may include: a data adjusting circuit configured to conditionally adjust a weight data value for a MAC (Multiplication and ACcumulation) operation based on comparing the weight data value to a reference data value, and generate flag information indicating whether the weight data value has been adjusted; a memory cell array circuit configured to store the adjusted weight data value outputted from the data adjusting circuit; and a data calculation circuit configured to recover, on the flag information, a result based on the weight data value from a result based on the adjusted weight data value to perform the MAC operation on an input data value and the weight data value.