247results about How to "Fast optimization" patented technology

An inexpensive and rapid method for fabricating arrays of hollow microneedles uses a photoetchable glass. Furthermore, the glass hollow microneedle array can be used to form a negative mold for replicating microneedles in biocompatible polymers or metals. These microneedle arrays can be used to extract fluids from plants or animals. Glucose transport through these hollow microneedles arrays has been found to be orders of magnitude more rapid than natural diffusion.

The invention discloses a method for determining technological parameters in a flow industrial process. The method includes the steps of firstly, collecting production data, and using the technological parameters as input and product quality and output to build quality models; secondly, using rule extraction to extract corresponding rules between the input and the output from the production data so as to form a rule library; and thirdly, using optimization to find rules corresponding to given quality indexes according to the given quality indexes, initiating the technological parameters in the range of the rules, using the initiated technological parameters as input of the quality models to predict product quality, calculating errors between the predicted quality and the quality indexes, and correcting to find optimal parameters to enable the errors between the predicted quality and the quality indexes to be minimum. By the method, product yield is improved effectively and production cost is lowered.

The invention provides a cooperative air combat firepower distribution method based on an improved multi-target leapfrog algorithm and belongs to the technical field of computer simulation and method optimization. The method comprises the steps that firstly, required data information is obtained through a cooperative air combat formation command and control system; secondly, a multi-target optimization module of cooperative air combat firepower distribution is established; then a multi-target quantum leapfrog algorithm based on a self-adaptive mesh method is carried out, and a Pareto non-inferior solution of firepower distribution problem is solved; finally, rules can be selected independently according to the optimal distribution scheme, and the optimal firepower distribution scheme is selected from the non-inferior solution. The cooperative air combat firepower distribution method based on the improved multi-target leapfrog algorithm has the major functions that weapons on a fighter aircraft on an attack mission are distributed to multiple targets according to the optimal firepower distribution scheme, the formed cooperative air combat is enabled to realize the optimal cooperative attack effect, and the maximum operational effectiveness is obtained.

The invention discloses a method and system for utility boiler combustion subspace modeling and multi-objective optimization, belongs to the field of utility boiler optimization operation, and particularly relates to a method and system for setting up of a high-precision combustion model and solution of multi-objective optimization. The method includes the following steps of determining input variables of a combustion optimization model, determining the variable to be optimized from all the input variables, dividing a load into a plurality of sectors with the neighborhoods overlapped, setting up a combustion subspace ANFIS model for each sector in an off-line mode, collecting data in real time, conducting partial subspace model modification in an on-line mode, conducting on-line multi-objective optimization by taking the constraint of a unit load into consideration, taking maximizing the boiler efficiency and minimizing the nitrogen oxide emission as targets, and utilizing a mature global optimization algorithm and on the basis of comprehensive cost minimization, and separating and implementing the optimization result. The method and the system are suitable for combustion optimized operation of a coal powder utility boiler and have the advantages of being high in modeling accuracy and high in optimization speed.

The invention relates to a vibration fault diagnosis method of a hydroelectric generating set. The method comprises the steps of: firstly, carrying out denoising processing on collected original vibration signals by utilizing a random resonance technology; secondly, carrying out characteristic vector extraction on the vibration signals after the denoising by utilizing a multi-dimensional permutation entropy technology; thirdly, establishing fault diagnosis models of optimized support vector machine based on an improved particle swarm algorithm; fourthly, inputting extracted characteristic vectors into the models of the models of optimized support vector machine based on the improved particle swarm algorithm for fault diagnosis. The method is applicable to the vibration fault diagnosis of the hydroelectric generating set, the diagnosis result is high in precision, the fault type of the generating set can be relatively accurately diagnosed, the reliable diagnosis result is provided to operation maintenance personnel of the generation set, the maintenance personnel can process faults timely and rapidly, and the safety and the economic performance of the operation of the generating set are ensured.

The invention relates to an L1/2-norm-based sparse linear array optimization method. The method is characterized by comprising the basic steps of determining an initial array and a weighting matrix, determining array weight vectors, judging whether the stimulus of head and tail array elements in the array weight vector is greater than a set stimulus minimum delta or not, judging whether an L1 norm for optimizing a difference between the previous and latter array weight vectors is smaller than a set error minimum xi or not, and determining the array element positions and stimulus of the sparse linear array. According to the method, the non-convex optimization problem of solution to an L1/2 norm is converted into a series of convex optimization problems of the L1 norm, so that a sparse array with lower sparsity can be obtained to reduce the number of actually required array elements on the premise of substantially keeping calculation unchanged; meanwhile, the head and tail array elements of the array are constrained and adaptively regulated under the condition of given array aperture, so that the problem of deficiency of the head and tail array elements of the sparse array in an iterative convex optimization process is well solved, and the method is particularly applied to the place of optimization of a large-sized antenna array.

The invention discloses a joint path selection and power distribution method for energy collection nodes in a wireless sensor network, and belongs to the field of cooperative communication technologies. The method comprises the steps of analyzing a system scene, describing problems; establishing a system mathematic model; and then finding the optimal solution by using an optimization method. The method aims at the special application scene and is derived from the actual application, and being different from the traditional independent sensor node or gateway resource distribution, the method comprehensively considers the joint power distribution and path selection of sensor nodes and gateways, and maximizes the handling capacity performance of the communication nodes by using the gateways as relay stations. According to the method of the invention, the solution of an optimization problem is processed by using convex optimization to convert a target function of the optimization problem without approximate calculation, so that computation complexity is greatly reduced while accuracy of the problem is not influenced, and delay generated by system overheads is reduced; a Lagrangian multiplier method is used in an optimizing process, and thus an optimizing speed is rapid; a subgradient method and an incremental step length are used in an iterative process, so that optimizing is more accurate.

The invention provides a reactive voltage optimal control method for a wind power plant cluster. The reactive voltage optimal control method comprises the steps that whether the reactive voltage optimal control for the wind power plant cluster needs to be carried out or not is judged; the reactive source equipment adjustment range of wind power plants and a pooling station in the wind power plant cluster region is obtained; and a reactive voltage optimal control mathematic model for the wind power plant cluster is built and solved. According to the reactive voltage optimal control method, a wind power plant cluster access point is used as a central voltage control node, the wind power plant grid-tied point bus voltage of the cluster region and a transformer tap of a booster station of the wind power plant are regulated, reactive compensation equipment of the pooling station is regulated to have reactive power, and a transformer tap of the pooling station is also regulated, the pilot node is enabled to meet the control instruction range of a dispatching mechanism, meanwhile the quiescent voltage stability margin of the cluster region is enabled to be maximum, and the active power transmission loss is enabled to be minimum; the quiescent voltage stability margin in the wind power plant cluster region can be effectively improved, the grid active loss in the cluster region also can be reduced, the operating safety and stability of a system are improved, and the capacity of digesting and saving wind power of the system is also improved.

The invention discloses an SQL to cloud environment mapping method. The method includes following steps: 1) rewriting the SQL statement to be transformed to obtain a plurality of rewritten HiveQL statement having the same function with the SQL statement to be transformed; 2) calculating the exercise price of each HiveQL statement and selecting the optimal statement for outputting. The SQL to cloud environment mapping system is also provided. The cloud environment statement (as HiveQL statement) can be quickly optimized while mapping the SQL statement to cloud environment for reducing actual input data size of the Mapper and Reducer and promoting the query performance.

The invention discloses a system for rapid optimizing of a maximum power point of a photovoltaic array under the shadow condition. The system for the rapid optimizing of the maximum power point of the photovoltaic array under the shadow condition is characterized in that the system comprises a photovoltaic cell set and an MPPT controller. The method for the rapid optimizing of the maximum power point of the photovoltaic array under the shadow condition comprises the steps of (1) preparation of data, (2) initialization of a program, (3) judgment of shadow covering, (4) adjustment of a duty ratio, and (5) searching of a maximum power point. The system and method for the rapid optimizing of the maximum power point of the photovoltaic array under the shadow condition have the advantages that the voltage of a position with the maximum power in the whole area can be found rapidly, the searching speed can be increased, searching accuracy can be improved, and the rapid optimizing of the maximum power point of the photovoltaic array under the shadow condition can be achieved without the need of extra arrangement of components.

The invention discloses a combined resource distribution method based on an energy acquisition cooperation communication system and belongs to the cooperation communication technology field. The method comprises steps of system scene analysis and problem resolution; system mathematics model establishment and optimal solution calculation on the basis of an optimization method. According to the method, for the special application scene from a practical application, compared with a relay selection method in the prior art, problems of high complexity and high network cost existing in relays in the prior art are solved, a single relay node selection algorithm and a corresponding resource distribution algorithm are searched from an easy-practical-application angle, single relay cooperation communication on the basis of energy acquisition is considered, a throughout expression under the scene is derived, optimal relay selection and power distribution are considered in a combined mode, and the method has great guiding meaning.

An apparatus, system, and method are disclosed for performing fast approximate computation of statistics on query expressions in order to improve query optimization within a database management system by accurately and quickly estimating the sizes of intermediate query results. This is accomplished by analyzing a query for join instruction and identifying a fact table and a dimension table within those join instructions. Then, frequency statistics corresponding to distinct values of within the fact table are retrieved from a catalog table. Those frequency statistics are used in combination with a full scan of the dimension table accurately and quickly estimate frequency statistics for an expected join between the fact table and dimension table. The estimated frequency statistics corresponding to the expected join may then be used in such operations as query optimization.

The invention discloses a cellular network energy efficiency optimization method based on relay cooperation and belongs to the cooperation communication technology field. The method comprises the following steps of establishing a system model; carrying out system scene analysis; carrying out problem resolution; and using a convex optimization method to solve an optimization problem. In the invention, a bit number transmitted per joule under maximized system time average is taken as a utility function, combined relay selection, carrier wave pairing and power distribution problems under an OFDM relay network scene of a plurality of relays and a plurality of users are combinedly considered and a realistic instructive significance is possessed. The method is different from a traditional relay protocol, a base station is allowed to retransmit information of a first time slot through idle subcarriers in a second time slot, emission power of the base station and the relay can be reduced and a system capacity is increased. An algorithm of the invention is designed reasonably and is easy to realize.

The invention relates to the technical field of battery state-of-charge estimation of an electric vehicle power battery system, in particular to an algorithm based on SOC and SOH joint estimation of apower battery. The method optimizes parameters of an RF algorithm through a TSBSO algorithm so as to optimize an algorithm pruning threshold, the number of pre-test samples and the number of decisiontrees, and the optimized algorithm can quickly find a globally optimal solution and improve the algorithm efficiency. The SOH of the power battery is estimated through the RBM, the RBM is optimized through the WOA, and model parameters are prevented from falling into local optimum and thus the purposes of correcting the maximum available capacity of the battery and improving the SOC estimation precision of the power battery under the full-time working condition are achieved; the SOC of the power battery is estimated through the combination of a TSBSO-RF H-infinity calculation method and filtering, the advantages of the two algorithms are exerted by adopting a linear fusion algorithm, the defects of the two algorithms are avoided and the SOC estimation precision of the power battery is higher.

This invention discloses an allocating method of united resource of a relay system based on optimal energy efficiency, and relates to the technical field of mobile communication. The method comprises the following steps: establishing a system model; analyzing a system scene; resolving problems; and solving an optimization problem by a convex optimization method. Compared with the traditional relay protocol, a base station is allowed to resend information of a first time slot through idle subcarriers during a second time slot; the transmitting power of the base station and the relay can be reduced; and the system capacity can be improved. The method uses an optimization model of the energy efficiency as a nonlinear mixed-integer programming problem; since the existing conventional method cannot be applied to solve the problem, and in order to reduce the complexity of the problem, the method first changes the optimization model into linear convex programming through using a Dinkelbach method, then solves the simplified linear programming problem based on dual programming, and finally works out an optimal solution based on the Hungarian algorithm and the subgradient algorithm. The method is reasonable in algorithm design, and is easy to realize.

The invention discloses a relay system energy efficiency optimization method based on the OFDM, and belongs to the technical field of mobile communication. The method comprises the steps: building a system model; carrying out the analysis of a system scene; summing up problems; and solving an optimization problem through employing a convex optimization method. The method combines the integrated channel state information under the constraints of the maximum total power and minimum user instant speed, gives consideration to the joint optimization problem of enabling the energy efficiency to be maximized while considering to the equity, and gives a mathematical expression of user equity. Aiming at the solving of the optimization problem, the method employs the convex optimization processing, converts a target function of an optimization problem, does not need to carry out approximate calculation, does not affect the precision of the problem, greatly reduces the calculating complexity, and reduces the time delay caused by the system expenditure. The method is reasonable in algorithm design, and is easy to implement.

The present invention relates to a genetic algorithm-based piezoelectric actuator feedforward and closed-loop compound control method and system. According to the method and system, a feedforward model and a PID (proportional-integral-derivative) closed-loop control system are adopted to form a feedforward and PID closed loop so as to perform feedforward and closed-loop compound control on a piezoelectric actuator, and therefore, the control accuracy of a piezoelectric ceramic controller can be improved; the current dominant feedforward and PID compound control algorithm is adopted, and a genetic algorithm is utilized to find optimal PID parameters, and therefore, closed-loop control over the piezoelectric ceramic actuator can be realized; and the genetic algorithm can find suitable functions within specified ranges, so that the genetic algorithm is adopted to set three PID coefficients, and therefore, better closed-loop control over the piezoelectric actuator can be realized.

The invention provides a disturbance-based intensity modulated arc therapy optimization method. Firstly an intensity modulated arc therapy optimization model is established according to conditions such as information on a target region and organs at risk, beam setting parameters and each organ dose (volume) constraint and hardware constraint; an initialized sub-field is obtained by using intensity distribution optimization. Then the shape of the sub-field is optimized by using disturbance, the weight of the sub-field is optimized by using a conjugate gradient method after determination of the shape, and finally the optimal solution for the intensity modulated arc therapy is optimized. According to the method, a mathematical model of an optimization problem is accurately established, the solving speed is high, the algorithm is stable and the robustness is strong.

The invention relates to an active load reducing control system and method for a large wind turbine blade. An optical fiber strain sensor measures a stress value of the root portion of the blade and transmits the stress value to a control unit; the control unit comprises a PID controller performing parameter optimization through a teaching and learning algorithm and a fuzzy controller for processing a strain force signal of the root portion of the blade; a flap swing angle is subjected to switching control through the fuzzy controller and the PID controller, and beneficial effects of fuzzy control and PID control are synthesized; meanwhile, a machine front wind field signal sensing device measures the front air speed of a wind turbine and transmits the front air speed to the control unit; a feedforward controller in the control unit calculates control quantities needed by uniform loads caused by reducing stochastic wind or turbulent wind by monitoring the change of the machine front air speed in real time; and the control unit couples the two parts of control quantities, and control over the flap swing angle is completed. The active load reducing control system and method for the large wind turbine blade effectively reduce the strain force of the root portion of the blade, the service life of the blade is prolonged, and the using cost of a wind turbine unit is reduced.