291results about How to "Prevent falling into" patented technology

The multi-parking-lot and multi-vehicle-type vehicle path scheduling control method comprises the steps of 1, establishing an objective function by taking the lowest total cost of all delivery vehicles as an objective; Step 2, performing a coding step; 3, performing population initialization; 4, evaluating all the individuals by adopting the objective function as a fitness function; Step 5, performing selection and crossover operation; step 6, performing mutation operation; 7, performing neighborhood search on each individual in the population by using an improved extreme value optimization algorithm; Step 8, calculating fitness of all individuals in the population; Step 9, performing selecting; Step 10, performing elite retention; Step 11, completing iteration in sequence; Step 12, judging whether a termination condition is met or not, the termination condition being that the number of iterations g reaches the maximum number of iterations MaxGen or the number of iterations Nu of whichthe Gb fitness value remains unchanged reaches the specified number of iterations Kbest, if yes, continuing to execute the step 13, and if not, returning to execute the step 5; Step 13, outputting the individual Gb and the fitness value fGb thereof; And 14, interpreting the optimal individual Gb and the fitness value fGb thereof. The invention aims to improve the search efficiency and convergencespeed of the algorithm.

The invention provides a support vector machine method based on chaos and grey wolf optimization, specifically,the grey wolf algorithm chaotization is combined with the support vector machine; two key parameters of penalty coefficient C and kernel width Upsilon of the support vector machine are optimized by the grey wolf chaotization algorithm with outstanding whole searching ability; the best extreme parameter value of the learning machine is obtained so that the application can obtain accurate and intelligent decision effect; the machine can help the decision mechanism effectively to make scientific decision, so the machine has important application value.

The invention discloses a method for quickly optimizing an overall maximum power point of a photovoltaic array under local shadow. Under the local overshadowing condition, output characteristics of the photovoltaic array present multiple peak points. For searching an overall maximum value, the method comprises the steps of adopting a modified fruit fly algorithm to perform overall range searching, confirming a range where maximum power is located, then finding a maximum power point in a sub-region in a confirmed region by improving a golden section method and using the maximum power point as a working point of the whole photovoltaic array. By adopting the two steps, the overall maximum power point of the photovoltaic array can be quickly optimized.

The invention provides a plate glass packing box, as well as a packing method, an unpacking method and an unpacking device for the plate glass packing box, which can be conveyed efficiently on the surface of a large-scale plate glass used for a flat-panel display (a liquid crystal display, an plasma display and the like) without damage or stain generation, and can be used for packing and unpacking the glass plate efficiently. The plate glass packing box is provided with a pedestal (2) carrying the glass plate (16), wherein a substantial flat bottom bearing plate (4) and a substantial flat back bearing plate (5) are arranged on the carrying surface (3) of the pedestal (2); the substantial flat bottom bearing plate (4) is used for bearing the end part of the glass plate (16); the substantial flat back bearing plate (5) is used for bearing the surface part of the glass plate (16); the bottom bearing plate (4) is arranged slantways relative to the carrying surface (3) of the pedestal (2), and is provided with a glass plate press component (17); and the glass plate press component (17) is used for pressing the front surface of the glass plate (16) on the bottom bearing plate (4), and can mounted and dismounted vertically relative to pillars (7) uprightly arranged at corners behind the pedestal.

The invention discloses an imitating method of a power amplifier and an imitating device of the power amplifier. The method adopts an improved back propagation (BP) neural network to imitate the power amplifier. The improved BP neural network adopts Levenberg-marquardt (LM) learning algorithm and training algorithm with momentum factors added to update weight values and threshold values of a model, and therefore model building speed is effectively increased and the model is prevented from being sunk into a local minimum. Disclosed is the imitating device of the power amplifier further. The improved BP neural network is adopted. The imitating device of the power amplifier is further used for building a power amplifier imitator with a parallel structure. Imitation and training are free of mutual interference. Working efficiency of the power amplifier imitator is improved. Compared with the prior art, the imitating method of the power amplifier and the imitating device of the power amplifier are quick in training convergence speed and good in instantaneity.

The invention discloses a storage box for logistics transportation. The storage box comprises a box body, a storage groove with an opening facing upward is formed in the box body, and a cover plate isrotatably connected to the opening of the storage groove; a pulling groove with an opening facing upward is formed in the cover plate, a pulling rod transversely arranged is fixedly connected to theinside of the pulling groove, and a sliding cavity with an opening facing downward is formed in the box body; an inserting rod is connected to the inner wall of the upper side of the sliding cavity through a first spring, an inserting groove matched with the inserting rod is formed in the upper side wall of the box body, and a sliding rod is further fixedly connected to the side wall of the inserting rod; a strip-shaped opening communicated with the sliding cavity is formed in the side wall of the box body, the sliding rod penetrates through the strip-shaped opening, and a locking device cooperating with the inserting rod is slidably connected to the inside of the inserting groove. The storage box is simple in operations and convenient to use, the stacking between two box bodies is simpleand firm, the slipping phenomenon cannot easily occur, the safety performance of the device is improved, the cargo safety is protected, the separation between the two box bodies is convenient and efficient, and the working efficiency is improved.

The invention discloses a power system economic load distribution method based on an improved whale algorithm. The power system economic load distribution method comprises the steps of establishing a corresponding constraint condition expression according to the requirement of a power system economic load distribution problem in practice; establishing an objective function of the power system economic load distribution problem according to the constraint condition, and converting an actual application problem into a solution of a nonlinear programming problem; proposing an improved whale optimization algorithm, and performing optimization solution on the power system economic load distribution problem by utilizing the algorithm; and updating the position by adopting a self-adaptive weight strategy through the improved whale optimization algorithm, updating the position again by an individual through a random differential variation strategy, obtaining the final position before and after the change, and further obtaining the optimal result of economic load distribution of the power system. In order to improve the search capability of the whale optimization algorithm, an adaptive weight and differential variation strategy is introduced, so that the algorithm can perform global search in the early stage and perform accurate local search in the later stage.

The invention relates to crushing equipment, in particular to high-efficiency crushing equipment for preparation of an instrument powder coating in order to achieve the technical effects of being goodin crushing effect and easy to operate. In order to achieve the technical effects, the high-efficiency crushing equipment for preparation of the instrument powder coating, provided by the invention,comprises a bottom plate and the like. The left and right sides of the top of the bottom plate are symmetrically connected with support plates. The tops of the support plates are connected with a crushing frame. The bottom of the crushing frame is provided with a net. The top of the crushing frame is connected with a frame body. The bottom of the frame body is provided with an opening. The top ofthe frame body is connected with a discharge hopper. The discharge hopper communicates with the frame body. A breaking device is mounted on the left side of the frame body. A breaking component of thebreaking device is located in the frame body. The high-efficiency crushing equipment can break raw materials through the breaking device. Moreover, the breaking device can drive a crushing device tooperate and crush the broken raw materials. Accordingly, the high-efficiency crushing equipment achieves the effect of being easy to operate.

The invention discloses an integrated energy microgrid scheduling method based on hydrogen energy and natural gas hybrid energy storage, and the method comprises the steps: carrying out the modeling of energy equipment of each unit in an integrated energy microgrid based on hydrogen energy and natural gas hybrid energy storage, and obtaining the operation initial information of each unit; determining an energy flow relationship of each unit; establishing an optimization scheduling model based on the environment cost and the operation cost; converting multiple targets into a single target by adopting a weight coefficient method; setting a safety constraint condition; and combining a difference operator in a random fractal search algorithm, and optimizing and solving the established optimalscheduling model to obtain an optimal scheduling strategy. According to the invention, an optimal scheduling scheme with both environmental protection and economy can be obtained for a hydrogen and natural gas hybrid energy storage integrated energy microgrid system, and the stable and efficient operation of the hydrogen and natural gas hybrid energy storage integrated energy microgrid is ensured;the convergence speed can be effectively improved, the algorithm is prevented from falling into local optimum, and the system operation cost is reduced.

The invention provides a prediction model method based on an improved moth optimization algorithm, which comprises the steps of loading a data set and performing standardized processing on sample data; Gaussian mutation strategy and chaotic agitation are used to improve the moth flame optimization algorithm, and support vector machine model and/or limit learning machine model are constructed by using the improved moth optimization algorithm. The implementation of the invention can not only increase the diversity of the population and enhance the searching ability of the algorithm, but also prevent the algorithm from falling into the local optimum and quickly finding the global optimum solution.

The invention discloses a disassembly tool for an oil drain plug of an engine oil bottom shell. The disassembly tool comprises a handle, a plug sleeve, an oil baffle disc and a locking ring, wherein the handle penetrates through the center of the oil baffle disc and is fixedly connected with the oil baffle disc; the part, positioned at the left side of the oil baffle disc, of the handle is a hexagonal nut; the part, positioned at the right side of the oil baffle disc, of the handle is a connecting cylinder; the left end of the plug sleeve is fixedly connected with the right end of the connecting cylinder; a stud is arranged on the left part of the plug sleeve; a hexagonal sleeve is arranged on the right part of the plug sleeve; a circular hole is formed in the inner wall of the hexagonal sleeve; a steel ball is embedded into the circular hole; the left part of the locking ring is provided with an inner threaded hole; the right part of the locking ring is provided with a tapered hole which is gradually increased in diameter from left to right, and communicates with the inner threaded hole; the locking ring penetrates through the hexagonal sleeve and is screwed on the stud through threads; the wall surface of the tapered hole can generate extrusion effect on the steel ball and can restrain the steel ball from dropping. The disassembly tool not only can prevent an oil drainage plug from dropping into an oil basin, but also can prevent hands of an operator from being burnt, and further can improve the working efficiency.

The invention provides a prediction method based on an orthogonal reverse bottleneck optimization algorithm, comprising the steps of loading a data set and performing standard processing on sample data; the penalty coefficients and kernel widths are optimized by using the orthogonal inverse bottleneck optimization algorithm, and a predictive support vector machine model is constructed. By adoptingorthogonal learning and reverse learning strategies to optimize the penalty factor and the kernel width on the basis of the traditional optimization algorithm of Styela bottlenecks, the invention caneffectively reduce the possibility of falling into local optimization in the optimization process, and obviously improve the quality of the solution and the convergence efficiency.

The invention discloses a system and a method for realizing electric energy meter abnormity diagnosis by applying a quantum particle swarm algorithm, and relates to the technical field of electric energy metering. An architecture system of the Internet of Things is constructed, remote monitoring of abnormal data of an electric energy meter is realized, change and extension of data information of the electric energy meter are realized by using a wavelet change method, noise interference can be suppressed by using wavelet transform, the feature extraction precision is improved, the accuracy is high, and the performance is more stable. An improved quantum particle swarm algorithm is used, particle swarms can be effectively screened; the convergence speed of the particle swarm is accelerated;according to the method, a BP neural network algorithm model is utilized to prevent simultaneous falling into local extremum, a good effect is shown in the aspects of convergence rate and global optimum searching, rapid diagnosis of abnormal data can be realized by utilizing the BP neural network algorithm model, a large amount of electric energy meter data information is rapidly calculated withina few seconds, and data analysis and judgment are realized.

The invention discloses a distribution center site selection method based on a bacterial foraging optimization algorithm. The method comprises the steps of 1) obtaining a distribution center and a historical distribution address set of a target city; 2) constructing a distribution center site selection model; and 3) implementing a bacterial foraging optimization algorithm. The method of the invention can perform modeling by using historical distribution addresses and a candidate distribution center and is more in line with distribution center site selection conditions in the presence of large-scale historical distribution addresses in reality, so that the site selection and the distribution can be combined to improve the accuracy of the site selection of the distribution center, reduce thedistribution cost, improve the timeliness of distribution, and improve customer satisfaction.

The invention provides a neural network-based wireless sensor network data prediction method. According to the method, a neural network is led into a wireless sensor network, and each wireless sensor datum is described through neurons, and a neural network model can be built; the fusion and extraction of acquired data of the wireless sensor network can be realized through using the neural network model of the wireless sensor network; motion items are added, and multiple factors are effectively considered, and not only is the gradient descent direction of a certain moment adjusted, but also a gradient direction before the moment is adjusted, and therefore, a vibration range can be authentically reduced, and training speed can be improved; and main factors that influence data output results are selected through differences between various kinds of application types, and a prediction model is established. The neural network-based wireless sensor network data prediction method of the invention can perform self learning in a certain field so as to obtain influence factors therein and construct complex nonlinear relationships, and therefore, influence of human intervention on prediction results can be effectively reduced, and the results are of greater objectivity.

The invention discloses a matrix warping winch observation system, which comprises a shore station system, a mother bomb system and a plurality of submunition systems. The shore station system is connected with the mother bomb system through an umbilical cord cable, and the plurality of submunition systems are carried by the mother bomb system before being released. A mast cartridge system includes a mast cartridge housing, A system control module is arranged on the upper part of the mast cartridge shell, and a air guide cover is arranged at the bottom of the mother shell case, and a first measuring sensor is arranged at the air guide cover, All the submunition systems are uniformly arranged along the circumference of the master shell, a release device for controlling the synchronous release of all the submunition systems is arranged at the middle part of the master shell, and a window for facilitating the submunition system to protrude from the master shell is arranged at a position corresponding to the submunition system on the master shell. The invention provides a method and a device for detecting the data of the whole sea depth space region, which effectively solves the attitude unity and synchronism of the simultaneous release of a plurality of submunition systems, and improves the accuracy of the measurement data of the submunition system.