50results about How to "Implement classification" patented technology

The invention discloses a building pipeline intelligent flaw detection and leakage positioning system, which relates to the technical field of building pipeline detection and comprises a data acquisition module, a multi-modal fusion module, a defect identification module, a leakage positioning module, a digital twinborn module, a health prediction module and a decision control module. The data acquisition module is used for deploying multiple types of sensors along a building pipeline, acquiring acoustic emission signals, infrared thermal imaging images, pressure fluctuation data and fluxgate detection signals in a running state of the pipeline, and outputting original sensing data; the multi-modal fusion module is connected with the data acquisition module and is used for performing feature extraction on the original sensing data, constructing a multi-modal feature vector, dynamically adjusting each modal weight based on environmental parameters and outputting a weighted fusion feature vector; and the defect identification module is connected with the multi-modal fusion module and is used for inputting the weighted fusion feature vector into a deep neural network model.

The application discloses a cigarette case intaglio printing surface quality evaluation method and system based on image features, and relates to the fields of cigarette case intaglio printing quality detection and machine vision technology; the application collects cigarette case intaglio printing images through an image acquisition unit and pre-processes the images into gray-scale images, extracts multi-scale gradient features to obtain a comprehensive feature index for preliminary defect determination, analyzes edge morphology and texture periodicity in a transition area to obtain a comprehensive defect discrimination index, obtains a defect score based on the multi-scale comprehensive feature index and the comprehensive defect discrimination index, and completes defect classification and positioning through spatial clustering and secondary verification; four quality grades are divided based on defect proportions and defect numbers, a defect labeling map, a heat map and a standardized quality evaluation report are generated, and the problem that extracted image features cannot effectively distinguish normal dots from defective dots and result in a high false detection rate is effectively solved, and the precision and efficiency of cigarette case intaglio printing surface defect detection are significantly improved.

The application discloses an expert warehousing method and system for petrochemical engineering. The experts to be warehoused are composed of application warehousing experts and designated warehousing experts with high-level professional technology. The method comprises the following steps: collecting basic information and work experience information of historical warehousing experts, analyzing the influence of the operation characteristics of the units to which the experts belong on the experience and professional skills of the experts, and determining multiple expert information classification items as expert extraction conditions; determining whether each application warehousing expert has the qualification of bid evaluation according to the sub-information under each classification item in the reported expert information of each application warehousing expert, then warehousing the experts with the qualification of bid evaluation and the sub-information under each classification item as the warehousing objects to form an initial expert warehouse; and updating the current initial expert warehouse by using the sub-information under the specific classification items configured for each designated warehousing expert, so as to complete the warehousing of experts. The application realizes the warehousing and classification of petrochemical engineering experts.

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.

The application provides an electrically connected steam drive thickened oil steam injection optimization method and system suitable for variable working conditions, and belongs to the field of thickened oil thermal recovery. The method comprises the following steps: constructing a partition variable working condition thermodynamic model of an electric heating furnace, a magnesium brick heat storage device dynamic heat storage and release model, a heat exchange steam production unit thermodynamic model and a heat transfer model along an injection wellbore; using a multiple variable working condition identification method facing the oil reservoir side, the energy side and the pipe network side to identify the working condition; using a model predictive control framework to perform real-time optimization on multiple targets facing multiple variable working conditions, and using a feedback correction mechanism to perform online correction on model parameters; using a scheduling optimization method facing multiple well steam distribution to distribute and schedule multiple well steam. The application can provide technical support for steam injection system operation optimization, energy cost control and power grid collaborative scheduling in the development of thickened oil steam drive, and has good engineering popularization value and application prospect.

The invention relates to the technical field of forge piece machining control, and particularly discloses an automatic control management system for vehicle forge piece machining, and the system comprises an online monitoring module which is disposed in a forging forming operation area of forge pieces and is used for carrying out the multi-dimensional real-time data collection of the forging forming process; the data processing and analyzing module is used for receiving and preprocessing the multi-dimensional real-time data, comprehensively analyzing the preprocessed multi-dimensional data and generating corresponding forging quality evaluation parameters; the state judgment module is used for comparing the quality evaluation parameters with a preset quality evaluation threshold range; real-time monitoring and self-adaptive optimization of the forging forming process are achieved, the quality threshold value and the sampling inspection frequency can be dynamically adjusted, and multi-dimensional sensing of the forging forming process, precise judgment and classification of the forging quality and self-adaptive optimization of the key threshold value are achieved.

The application provides a workpiece tightening defect classification method, system, controller and storage medium, wherein the classification method comprises: acquiring a first tightening defect curve and preprocessing the first tightening defect curve; cutting the preprocessed first tightening defect curve based on a preset rule to obtain a target tightening defect curve; extracting time domain features in the target tightening defect curve; and inputting the time domain features into a plurality of pre-trained defect recognition models respectively to obtain recognition results, wherein the recognition results comprise a target defect type corresponding to the first tightening defect curve or a defect type that the first tightening defect curve belongs to is not determined. The application solves the problem in the prior art that workpiece tightening defect classification cannot identify new defect types, resulting in defect classification errors.

The utility model discloses a kind of special treatment tray of diabetes nursing personnel, including treatment tray body, several test tubes, disinfection cotton swab, disinfection cotton ball and disinfection cotton yarn, first baffle is equipped in treatment tray body, and treatment tray body is divided into dirt area and clean area in the upper and lower sides of first baffle.The utility model divides treatment tray body into dirt area and clean area by first baffle, places small tray and sponge body in clean area, places several test tubes in several circular insertion slot, disinfection cotton swab and disinfection cotton ball are placed in first recess and second recess respectively, and syringe and injection medicine bottle are placed in small tray, separate with second baffle, load seat is placed on the long side of dirt area with U type clamping groove clamping, it is convenient to place several disinfectant bottles in several circular load grooves, realize the classification and separate placement of medical supplies, convenient and fast identification and use, effectively isolate sterile and germ area, avoid cross infection.

The utility model discloses a food weighing and grading equipment, including first chain plate conveyer, first chain plate conveyer one side is provided with platform scale, and platform scale one side is provided with material grabbing manipulator, and the both ends of platform scale are provided with qualified grading assembly and substandard product grading assembly respectively, and substandard product grading assembly and qualified grading assembly structure are same, qualified grading assembly includes second chain plate conveyer at first chain plate conveyer one end, and one end of second chain plate conveyer is fixedly connected with fixed frame, and the bottom of fixed frame is installed with visual inspection camera, and the outer wall of visual inspection camera is provided with illuminating lamp, and the bottom of visual inspection camera is provided with placing frame, and the bottom of placing frame swing joint has fixed seat, and the inside fixed seat is installed with third motor, and one end of third motor axle is connected with second connecting frame, and one end of second connecting frame is installed with second motor. The device can realize automatic weighing and ketone body classification after livestock slaughtering, thereby improving classification precision and classification efficiency.

The utility model relates to the technical field of paper currency identification, and discloses an adjustable multi-currency automatic identification and classified storage mechanism, which comprises a machine body, a first conveying device is arranged in the machine body, a second conveying device is arranged on the lower side of the first conveying device, a third conveying device is arranged on the lower side of the second conveying device, and a third conveying device is arranged on the lower side of the third conveying device. An inclined plate is fixedly connected between vertical plates on the two sides of the machine body, and through cooperation of a suction fan, a second connecting pipe, a rotating flange, a conveying roller, an air suction opening, an arc-shaped plate and other structures, single paper money stripping is achieved through controllable adsorption force (dynamic adjustment can be conducted according to paper money materials). And the adsorbed banknotes are conveyed to the upper side of the second conveying device, so that the recognition accuracy of the subsequent recognition module on the banknotes is effectively improved, and the separation effect is improved more remarkably.

The present application relates to the cross technical field of software testing and intelligent optimization algorithm, disclose a kind of unmanned plane training parallel program particle swarm test case generation method, comprising: first, based on the similarity of variation path determines convergent path pair and divergent path pair;Then, the above path pair is established to generate multiple task mathematical model for covering multiple path test case;Finally, based on the double-layer multi-population particle swarm algorithm collaborative evolution executes mathematical model solution.The present application is aimed at the multi-process feature of parallel program, through path similarity screening, multi-task modeling and the layered optimization strategy of double-layer particle swarm collaborative evolution, can efficiently generate test data covering multiple target paths, significantly improve the integrity and execution efficiency of software testing, especially suitable for the testing scene of complex software such as parallel program.

The utility model relates to the technical field of sample classification, in particular to a food sampling inspection sample classification coding device which comprises a storage box, a plurality of ejection mechanisms are connected to the bottom of the inner wall of the storage box, vertical grooves and inserting grooves are formed in the two sides of the storage box, moving mechanisms are arranged in the two vertical grooves, and the moving mechanisms are arranged in the inserting grooves. A storage frame is connected between the two moving mechanisms, the multiple ejection mechanisms all extend into the storage frame, and locking mechanisms are arranged on the two moving mechanisms. A plurality of sampling tubes embedded in the storage frame can be easily ejected out from the corresponding transparent plates by a worker, so that the worker can conveniently take the collected sampling tubes and clearly know the serial number of each sampling tube, samples are classified, and meanwhile, the sampling efficiency is improved. And the convenience of taking out the plurality of sampling tubes is also improved.

The application belongs to the technical field of image processing, and provides an image classification method and system based on source domain independent field adaptation and active learning. The method comprises the following steps: based on unlabeled target domain medical image samples, a source domain model is used to select samples at one time; a feature extractor is used to extract the one-time selected samples to obtain the features of all samples; clustering operation is performed on the features of all samples to obtain pseudo labels of all samples; the value of neighbor uncertainty of each sample is calculated, when the value of neighbor uncertainty meets a certain range, the sample corresponding to the value of neighbor uncertainty is selected for relaxation operation, and the candidate label in the pseudo label is selected to perform subsequent labeling to obtain all labeled samples; according to the unlabeled target domain medical image samples and the medical image samples queried by active labeling, all labeled samples are combined, a target domain model is used, a loss function is calculated, and a trained target domain multi-label classification model is obtained for image classification.

The application relates to an automatic text classification method based on a car community, which comprises the following steps: obtaining a data set of car community texts; obtaining word vectors and text feature vectors as input values of a double-layer clustering model; performing clustering calculation on the word vectors and the text feature vectors to generate word classification and text classification respectively, so as to form the double-layer clustering model. When a new text enters: calculating the word vectors and the text feature vectors of the new text; calculating the word classification of each word vector of the new text and the word frequency under each classification; calculating the text classification of the new text; performing dynamic analysis according to the word classification, the word frequency and the text classification of each word vector of the new text; when the number of words and the word frequency of the new text generated outside the existing word classification reach a threshold value, the double-layer clustering model is updated. Therefore, the application can realize automatic classification of car community texts in the whole process, improve the classification accuracy and efficiency, and form a closed-loop management.

The invention discloses a multi-extended target joint tracking and classification method based on star convex RHM and LMB filters, and belongs to the field of radar target tracking. According to the method, an LMB parameter set is initialized by using target prior information, and then a sensor measurement set is divided through a mean shift algorithm; then, state prediction is achieved by combining survival target parameter updating and new target parameter sampling, and then measurement updating is completed through LMB-to-GLMB, GLMB updating and GLMB-to-LMB; and then trimming and fusing the LMB parameter set, estimating the number of targets, extracting state information, and circularly executing until observation is finished. According to the method, a star convex RHM modeling expansion state is adopted to reduce dimensions, the low detection probability / high clutter scene performance is improved based on an LMB framework, the tracking classification effect and the real-time performance are both considered, and the engineering application value is high.

A method and apparatus for slope disease identification based on UAV and machine vision technology includes a UAV equipped with a high-resolution camera that acquires multi-angle images of a slope area along a preset flight path; preprocessing the images, extracting features, and enhancing the images; identifying and classifying disease features using an improved YOLOv8-seg instance segmentation algorithm, covering slope diseases such as cracks, landslides, and collapses; quantifying the risk level of slope diseases based on the identification results using rule models or multi-factor analysis methods; and using a Long Short-Term Memory (LSTM) network to dynamically predict the changes in the acquired time-series images of the diseases, predicting the development trend and potential instability time. Based on the image data acquired by the UAV, real-time monitoring and dynamic analysis of slope diseases are performed, enabling timely detection of potential hazard areas and accurate identification of disease features, avoiding subjective errors that may be caused by human judgment in traditional methods.

The utility model belongs to the technical field of building engineering, especially related to a building engineering waste treatment equipment, include: support frame, support frame one end rotatory connection gear two, support frame upper end fixed cylinder, cylinder inner chamber rotatory connection auger blade one, cylinder one side rotatory connection mounting disc two, mounting disc two sleeve gear one, and fixed, gear one and gear two meshed connection, mounting disc two one side install sieve rod, sieve rod one end install mounting disc one, auger blade one one end fixed auger blade two. The utility model has the spiral conveying and the rotary screening integrated structure realization building waste's continuous processing and classification, convenient to adjust the screening size simultaneously, save time and labour, has improved the work efficiency's advantage.

The application discloses a kind of based on time scale SiC power MOSFET single pulse UIS failure behavior determination method, by in the single pulse non-clamping inductance switching test of SiC power MOSFET, determine the final avalanche resistance time, and then obtain the failure behavior of single pulse non-clamping inductance switching.The application solves the problem of avalanche failure mechanism determination method for SiC power MOSFET under single pulse non-clamping inductance switching.Perfect the reliability evaluation theory system of wide bandgap semiconductor device.Realize the quick prediction from macroscopic electrical parameter to microscopic physical failure, solve the problem of long time-consuming and destructive in the prior art, just need to extract "avalanche resistance time t av In macroscopic electrical test, the critical failure temperature and specific physical damage inside the device can be predicted, the failure behavior of SiC power MOSFET avalanche failure behavior is distinguished and classified, and the efficiency of failure analysis is greatly improved.

The invention relates to the technical field of geographic information system and seismological observation application, in particular to a data resource pool building system which comprises a data acquisition module, a non-seismic event exclusion module, a physical performance detection module and an abnormal reason tracing module. According to the method, seismic waveform original data are periodically collected, storage duration comparison is carried out, seismic observation data categories are judged based on multi-dimensional parameters, physical performance fault categories are identified through hardware, software and architecture state parameters, and the method specifically comprises the steps of extracting and analyzing data geographic positions to judge scheduling paths, identifying and clearing repeated observation contents, and determining the physical performance fault categories. Calculating waveform stacking pressure and signal writing skew, judging frequency domain sorting delay, calculating a time adjustment factor based on frequency drift and correcting a storage time threshold value; through multi-dimensional data verification and load optimization, dynamic adjustment of a data storage time threshold is realized, and data storage efficiency and system stability are improved.

This application discloses a method, apparatus, device, storage medium, and program product for classifying pathological images, relating to the field of machine learning. The method includes: acquiring sample pathological images from a pathological image database, the sample pathological images being labeled with sample tags; matching the sample tags with corresponding pathological image tag sets in the pathological image database to determine the sample pathological image database; inputting the sample pathological images into a classification model to obtain sample prediction probabilities; determining a loss value based on the sample prediction probabilities and sample tags corresponding to the sample pathological image database, training the classification model to obtain a pathological image classification model, which is used to classify target pathological images to obtain prediction results. Through this approach, the correlation between pathological image databases can be strengthened, achieving better centralized pathological image classification and facilitating better management and use of pathological images. This application can be applied to various scenarios such as cloud technology, artificial intelligence, and intelligent transportation.

The Micro LED detection device comprises a base, a feeding and discharging area and a detection area are sequentially arranged on the base in the X-axis direction, a multi-axis transfer mechanism and a storage mechanism are arranged in the feeding and discharging area, a clamp and a product adsorption assembly are arranged at the tail end of the multi-axis transfer mechanism, and a transfer mechanism and a detection mechanism are arranged in the detection area in the X-axis direction. Automatic feeding of products is achieved through the multi-axis transferring mechanism, the transferring mechanism is provided with the rotatable transferring assembly and the transferring carrying assembly, discharging of the detection mechanism can be achieved while feeding of the multi-axis transferring mechanism is achieved, meanwhile, the carrying mechanism is arranged in the storage mechanism, the products can be classified, and by means of the mode, the production efficiency is improved. According to the detection device, automatic detection and classification of Micro LED transverse group screens can be achieved, full-automatic feeding and discharging can be carried out in the detection process, the working efficiency of the detection device is remarkably improved, the production and preparation cost is reduced, and therefore large-scale mass production is achieved.

The utility model relates to the technical field of mechanical engineering, and discloses silicon material crushing double-shaft staggered tooth roller type crushing equipment which comprises a slope shell, the bottom of the slope shell is communicated with a hollow shell, the front end and the rear end of the right side of the outer wall of the hollow shell are fixedly connected with second waterproof shells, and the bottom of the hollow shell is communicated with a supporting shell. A crushing mechanism is arranged on the inner wall of the hollow shell and used for crushing objects to different degrees, a control mechanism is arranged on the inner wall of the bevel shell and used for controlling the feeding speed, the crushing mechanism comprises a partition plate, and the outer wall of the partition plate is fixedly connected with the inner wall of the bevel shell. Materials are poured into the right partition plate, the first motor is started, the rotating shaft and the first crushing roller work cooperatively to crush the materials, and if a higher crushing degree is needed, the materials are poured into the left partition plate, the second crushing roller, the second crushing blocks and the protruding blocks to crush the materials together.

The application discloses a kind of based on the high-efficiency operation method and system of sewage plant water inlet characteristics, solve the problem that sewage plant operation uses static single processing scheme, cannot adapt to different water inlet characteristics, including steps: setting water inlet classification standard, establish the parameter control database of sewage plant operation;Collect sewage plant water inlet data, according to water inlet data carries out water inlet characteristic analysis, and according to water inlet characteristic carries out classification;According to the type of water inlet characteristic at current time, from parameter control database corresponding sewage plant operation strategy is retrieved, water inlet characteristic is matched with sewage plant operation process parameter, then according to effluent target, the process parameter is fine-tuned;The effluent quality of sewage plant is predicted, according to the feedback regulation of predicted result to sewage plant operation process parameter.It realizes that sewage plant high-efficiency operation is strong in adaptability, energy-efficient, improves the operation efficiency of sewage plant and the treatment effect to sewage, reduces energy consumption and operating cost.

This invention discloses an intelligent loading and unloading robot, including a material bin, a conveyor belt rotatably mounted inside the material bin, a multi-axis robotic arm rotatably mounted on the top of the material bin, a second support plate fixedly mounted inside the material bin, and bearing plates slidably mounted on both sides of the second support plate; it also includes a sorting mechanism for sorting materials; the sorting mechanism includes a first mounting frame, which is fixedly mounted on one end of the multi-axis robotic arm, a sliding rod and a bidirectional threaded rod rotatably mounted inside the first mounting frame, a second motor fixedly connected to one end of the bidirectional threaded rod, and two first clamping plates threadedly connected to the outer surface of the bidirectional threaded rod; by causing the toothed ring to rotate around the detection rod, the detection rod can detect the entire exterior of the material, and then the multi-axis robotic arm transfers the material to the top of the conveyor belt. For qualified and unqualified materials, a lever is used to move them to the top of the two bearing plates respectively, thereby achieving material sorting.

The application provides a channel scene classification method based on multi-modal scene features and application, comprising: acquiring channel impulse response data and a three-dimensional terrain map; determining a steady-state interval of the channel; extracting channel characteristic feature parameters according to the steady-state interval of the channel; calculating geometric-physical environment feature parameters; combining the channel characteristic feature parameters and the geometric-physical environment feature parameters to construct a multi-modal scene feature dataset; performing dimension reduction processing on the multi-modal scene feature dataset by using a principal component analysis method; performing clustering analysis on the dimension-reduced multi-modal scene feature dataset by using a clustering algorithm; and parameterizing the channel scene obtained by clustering by using the geometric-physical environment feature parameters in the multi-modal scene feature dataset. The application simultaneously considers geometric-physical environment features and channel characteristic features, and can realize adaptive channel scene classification in a complex environment.

The utility model discloses an inductor surface defect detection device, which relates to the technical field of inductor surface defect detection and comprises a mounting component, the mounting component comprises a bottom plate, side plates are fixedly mounted on two sides of the bottom plate, and a top plate is fixedly mounted at the tops of the side plates. A rotating assembly is fixedly mounted in the middle of the top end of the bottom plate, a mounting hole is formed in one side of the top plate, two universal joint assemblies are fixedly mounted in the mounting hole, camera assemblies are fixedly mounted on one side of the bottom of the rotating assembly and the bottoms of the universal joint assemblies, and each camera assembly comprises a camera. An annular light supplementing lamp is fixedly installed on the outer side of the camera, the light emitting direction of the annular light supplementing lamp is consistent with the camera shooting direction of the camera, and a control panel is fixedly installed on the top of one end of the top plate. According to the utility model, the illumination can uniformly cover the detection station, the detection error caused by non-uniform light distribution of the traditional detection device is avoided, and the practical value is higher.

The utility model relates to the technical field of crop sorting, and discloses an efficient material sorting device which comprises a bottom plate, two fixing columns are fixedly connected to the top of the bottom plate, two limiting plates are fixedly connected to the outer portions of the two fixing columns, and two springs are arranged on the outer portions of the two fixing columns in a sleeving mode. Fixing blocks are slidably connected to the exteriors of the two fixing columns, one ends of the springs are fixedly connected to the exteriors of the fixing blocks, the other ends of the springs are fixedly connected to the exteriors of the limiting plates, a placing table is fixedly connected to the top of the bottom plate, and a rotating assembly for providing rotating capacity is arranged at the top of the placing table. The outer portion of the rotating assembly is rotationally connected to the inner wall of the fixing block. According to the material sorting and screening device, the problem that when part of materials are packaged, due to the fact that the sizes and the shapes of the materials are not uniform, a large number of materials cannot be quickly and accurately sorted and screened is solved through the structure.

The invention discloses a secondary safety measure area image intelligent identification method, system and device based on area positioning equal-ratio comparison and a medium, and belongs to the technical field of electric power inspection automation, and the method comprises the steps: collecting a field equipment image of a secondary safety measure, carrying out the preprocessing of the field equipment image of the secondary safety measure, and obtaining a pre-processed field equipment image of the secondary safety measure; the method comprises the following steps: extracting a salient region in an image, obtaining image sub-modules through region positioning and module partitioning, carrying out region positioning and feature extraction, carrying out character recognition, processing a recognition result, outputting character information, carrying out target component recognition on the image sub-modules, extracting component state information, and forming a structured recognition result; and verifying the consistency of the identification result based on the preset secondary safety measure rule, and outputting the verification conclusion, the method achieves the structural analysis of the image information through region positioning, feature extraction and character identification, converts the traditional manual verification into an intelligent process, and improves the operation safety and efficiency.

The embodiment of the application discloses a method and device for obtaining a cell classification model, the method comprising: obtaining a trained cell classification model; obtaining M feature maps of a target to be classified according to test data and the cell classification model; M is a positive integer greater than or equal to 1; the test data comprises one or more targets to be classified; obtaining the weights of the M feature maps; inputting the M feature maps with weights into the cell classification model, optimizing the cell classification model, and thus obtaining an optimal cell classification model. Through the embodiment, the classification of a target with a small inter-class gap is realized, and the classification efficiency and accuracy are improved.

The application belongs to the technical field of garbage disposal, and particularly relates to a distributed garbage collection and transportation system based on data cooperation, which comprises a mother box and a child vehicle. The child vehicle comprises a tracked mobile chassis, a speed difference separation mechanism, a cloud platform rotating mechanism, a positioning and navigation module, a full overflow detection module, an electric quantity monitoring module and a child box control module. The mother box and the child vehicle are both provided with a wireless communication module. The tracked mobile chassis is located at the two sides of the bottom of the child vehicle. The speed difference separation mechanism is located above the inside of the child vehicle. The cloud platform rotating mechanism is located below the speed difference separation mechanism. Through the cooperative operation of the child vehicle and the mother box, a '1+1' distributed child-mother box cooperative operation mode is formed. Through the tracked mobile chassis, the design principle of 'increasing the contact area, strengthening the traction force and optimizing the support structure' is used to effectively solve the problems of traffic, bearing and durability of the vehicle under complex terrains such as lawns, gravel roads, slopes and step edges.