40results about How to "Avoid maladaptive" patented technology

The invention relates to an EHV (Extra-High Voltage) power grid fault rule mining method based on a rough set association rule. According to the method, a distributed data mining idea is adopted, historical fault data of an EHV power grid is subjected to fault rule mining by using an association rule mining method based on a rough set theory, a distributed decision table is subjected to attribute reduction by using an attribute reduction algorithm based on an information entropy, and then, an Apriori algorithm in association rules is applied to the decision table, which is subjected to reduction, so as to carry out fault rule extraction. According to the method, the problem of inadaptability to large-data-volume historical fault databases of traditional data mining methods can be solved effectively, the complexity of rule extraction is lowered, and the method has the advantage of high fault rule mining efficiency.

The invention discloses an expressway tunnel and tunnel group operation environment visual scene simulation method which comprises the following steps of: (1) describing the expressway tunnel and tunnel group operation environment; (2) analyzing a virtual reality simulation technology key model; and (3) establishing an expressway tunnel and tunnel group operation environment simulation database system. An expressway tunnel and tunnel group operation environment visual scene simulation system comprises a three-dimensional visual scene model storage platform and a user instruction platform and visual scene simulation data generation platform. Through the invention, the application of the virtual reality technology in terms of highway tunnel visual scene simulation is perfected.

The invention provides a feature selection and weight calculation method of an imbalance text set, and belongs to the field of text information processing. In order to solve the classification problem of imbalance text data, a feature selection and weight calculation method and system are provided. The category discrimination degree and the average word frequency factor are combined, the chi-squared statistic method is improved so as to conduct feature selection, meanwhile, a commonly-used feature weight calculation method is improved, and on the basis of the improvement, the TF-IDF weight calculation method is provided. The effect of the method on solving the imbalance data set problem is superior to that of a traditional feature selection method, and the method is effective and feasible in effectively improving the classification accuracy.

The invention belongs to the technical field of joint dysfunction therapeutic devices, and particularly relates to a joint dysfunction fine adjustment type static drawing support. The joint dysfunction fine adjustment type static drawing support comprises a lower limb surrounding sleeve and an upper limb surrounding sleeve, wherein a lower joint bracket and an upper joint bracket are respectively arranged on the lower limb surrounding sleeve and the upper limb surrounding sleeve and are movably connected through a joint shaft to form a bendable joint assembly; a plurality of buckling band rings are respectively arranged on the lower joint bracket and the upper joint bracket; a plurality of deep slot pulleys are fixed arranged on the lower limb surrounding sleeve and the upper limb surrounding sleeve and are connected through traction ropes to form a pulley group; the lower limb surrounding sleeve or the upper limb surrounding sleeve is provided with a stepping type rope winding rotating wheel. The joint dysfunction fine adjustment type static drawing support is simple in structure, low in cost, easy to operate, safe, reliable and good in treating effect.

A polymorphous Hanson yeast expressed recombinant cholera toxin B subunit gene (CTB) is disclosed. In order to increase the expression of CTB in Hanson yeast, the coding gene of CTB is redesigned according to the application method of codon for the high-expression gene of Hanson yeast. The expression product can be used for preventing the diarrhea caused by cholera ribro and as the immune vaccine.

The invention discloses a reinforcement method of TRC for improving an anti-seismic performance of multi-piece brick masonry wall, and belongs to the technical field of repair, reinforcement and construction of masonry walls. The reinforcement method comprises the steps that a plurality of penetrating circular holes are drilled in the wall to be reinforced, and fiber reinforced plastic (FRP) rib anchor rods are used for penetrating through the circular holes; the surface of the wall to be reinforced is coated with high-performance concrete, a fiber woven net is impregnated with epoxy resin, and the surface of the fiber woven net is coated with the high-performance concrete again; If one layer of fiber woven net can not meet the requirement of wall anti-seismic performance improvement, twoor more layers of fiber woven nets can be laid; and wet water curing is carried out until the high-performance concrete age is reached. According to the reinforcement method of TRC for improving the anti-seismic performance of the multi-piece brick masonry wall, in-plane shear resistance and out-of-plane bending resistance of the multi-piece brick masonry wall are improved, the risk of serious damage or even collapse of a masonry structure in earthquake is reduced, the inadaptability of a masonry material caused by the use of the epoxy resin in FRP reinforcement is avoided, deficiency of low reinforcement efficiency of engineered cementitious composite (ECC) reinforcement is effectively improved, and the integrity of multi-piece brick masonry wall is improved.

The invention belongs to the field of unmanned vehicle simulation testing, and particularly relates to a vehicle hardware-in-the-loop simulation training system and method based on deep reinforcement learning. The system comprises a virtual simulation unit and a real vehicle controller, wherein the virtual simulation unit comprises a simulation vehicle module, a simulation control module, a real vehicle track database, a simulation sensor module, a reset interface and a start-stop interface. The real vehicle controller and the virtual simulation scene are subjected to joint simulation training, effective operation of the deep reinforcement learning movementplanning model in a real vehicle unmanned driving system is achieved, and therefore the problem that the deep reinforcement learning model cannot be effectively transplanted from a virtual simulation vehicle to an unmanned real vehicle is solved.

The invention provides a NandFlash encryption file system of adopting a random salt value. For the physical characteristics of NandFlash different from ordinary disk storage equipment, a JFFS2 file system is migrated into the NandFlash and used as a bottom-layer storage system thereof, the problems of inadaptability of directly applying the NandFlash to embedded equipment are solved, a national-password SM4 algorithm and SM3 algorithm are adopted on file encryption algorithms, then combination of a user password and the random salt value is adopted to generate a 128-bit user key in a process of generating the user key, the security hidden-troubles of directly storing user passwords and results after hash processing by original algorithms are avoided, and security of giving the user key bythe system is further improved.

The invention discloses a time series classification method and device. The method comprises the following steps of: aiming at a to-be-classified test time series, determining a first dynamic time regular distance between the test time series and each training time series in a pre-obtained training time series set; aiming at each determined first dynamic time regular distance, determining a first Gaussian function on the basis of the first dynamic time regular distance, and obtaining a Gaussian kernel transformation matrix of the test time series; obtaining a sparse representation coefficient matrix of the test time series according to the Gaussian kernel transformation matrix and a dictionary matrix of the pre-generated training time series set; aiming at each type, determining a residual error between the test time series and the type according to an atom, corresponding to a position of the type, in the dictionary matrix and the sparse representation coefficient matrix; and determining the type corresponding to the minimum residual error as a type of the test time series. By applying the time series classification method and device provided by embodiments of the invention, the time series classification accuracy can be improved.

The invention discloses a method for optimizing oil layer pressure plugging and displacement technical modes. According to the method, according to data such as well group reservoir development, wellnetwork conditions, development status, residual oil distribution situations and water flooded layer interpretation, the high water flooding invalid circulation part of a well group is determined, theseven pressure plugging and displacement construction technical modes are put forward, condition judging is conducted according to the simple invalid circulation part and the residual oil distribution situations, and a target reservoir single well or the well group are quickly matched with the reasonable 'pressure plugging and displacement' construction technical modes. The problem that at present, by adopting the technical mode of oil well pressure plugging or oil well pressure displacement for a single well, potential tapping cannot be effectively conducted on residual oil of a complex wellgroup is solved.

The present invention relates to the technical field of special wild boar sow feeding methods, in particular to a special wild boar sow feeding method for preventing special wild boar piglet white diarrhea. A delivery room is treated before parturition of a special wild boar sow; the sow is treated before parturition; feeding of the sow before and after parturition is controlled; and a fresh chinese pulsatilla root is decocted, and the obtained decocted soup is mixed to the fine feed of the sow to feed the sow, so that defects that the piglet is poor in the resistance and anti-stress ability caused by directly using medicine on the piglet is avoided. The piglet is directly fed with breast milk of the special wild boar sow, the physiology of the special wild boar piglet is improved, the immunity and anti-stress ability of the special wild boar piglet are enhanced, and the morbidity of white diarrhea of the special wild boar piglet is lowered, thereby lowering the cultural cost of the special wild boar, and promoting the rapid development of the special wild boar breeding industry.

The invention discloses a differential pressure measuring device and a differential pressure measuring method based on solenoid valve control. The differential pressure measuring device comprises an electromagnetic valve, a pressure sensor, air tubes, a data processing module and a data line. With the differential pressure measuring device and method of the invention adopted, the problem of maladjustment in internal and external differential pressure measurement of an aerostat capsule existing in a traditional measuring device can be effectively solved, and a real-time requirement under a special working environment can be satisfied.

The invention discloses a method for constructing a drilling fluid formation oil identification plate for drilling oil layer identification and a drilling oil layer identification method. The method for constructing the plate comprises the following steps: adding base oil with different masses into original drilling fluid, and respectively carrying out T1-T2 two-dimensional nuclear magnetic resonance measurement to correspondingly obtain a drilling fluid water signal centroid and a base oil signal centroid; adding formation oil with different masses, densities or viscosities into an original drilling fluid, and respectively carrying out T1-T2 two-dimensional nuclear magnetic resonance measurement to correspondingly obtain a formation oil signal centroid; and projecting the drilling fluid water signal centroid, the base oil signal centroid and the formation oil centroid into a preset rectangular coordinate system in a distinguishable manner, and constructing to obtain a drilling fluid formation oil identification plate. The method overcomes the inadaptability of T2 one-dimensional nuclear magnetic resonance to on-line measurement and an oil-based drilling fluid system, and is simpler to operate, lower in cost, more accurate in identification and wider in application range.