144 results about "Linear problem" patented technology

The present invention applies a novel iterative algorithm to the problem of multidimensional optimization by supplying a strict, nonlinear mathematical solution to what has traditionally been treated as a linear multidimensional problem. The process consists of randomly selecting a statistically significant sample of a prospect list, calculating the value of the utility function for each pair of an offer and selected prospects, reducing the original linear multidimensional problem to a non-linear problem with a feasible number of dimensions, solving the non-linear problem for the selected sample numerically with the desired tolerance using an iterative algorithm, and using the results to calculate an optimal set of offers in one pass for the full prospect list.

The invention relates to a fluid thermal motion simulation system based on the SPH algorithm and belongs to the field of thermodynamics simulation and visual flowing. The method comprises the steps of conducting modeling on fluid according to calculation examples and calculation requirements, solving a fluid control equation and a modified equation based on the SPH algorithm to achieve analogue simulation of fluid Lagrange thermal motion, and finally showing the thermal motion process of fluid visually in the form of graphs and animations by means of the visual processing technology. Compared with an existing meshing CFD simulation system, the fluid thermal motion simulation system has the advantage that a more reasonable simulation result can be obtained when the system is used for simulating certain advanced non-linear problems such as the jet flow problem, the ocean motion problem, the dam break problem and the dynamic boundary problem. Compared with an existing mesh-free CFD simulation system, the fluid thermal motion simulation system has the advantages that calculation stability and calculation accuracy are improved, and the gap of fluid thermal motion simulation and turbulent flow simulation is filled.

Systems and methods are disclosed for using machine learning (e.g., neural networks and/or combinatorial learning) to solve the non-linear problem of predicting the provisioning of a server farm (e.g., cloud resources). The machine learning may be performed using commercially available products, such as the SNNS product from The University of Stuttgard of Germany. The system, which includes a neural network for machine learning, is provided with an identification of inputs and outputs to track, and the system provides correlations between those. Rather than static rules, the machine learning provides dynamic provisioning recommendations with corresponding confidence scores. Based on the data collected/measured by the neural network, the provisioning recommendations will change as well as the confidence scores.

The invention discloses a motor position servo system self-adaptive control method based on an interference observer. The motor position servo system self-adaptive control method based on an interference observer includes the steps: establishing a mathematical model for a motor position servo system; constructing an interference observer and a self-adaptive controller based on the interference observer; and by means of a Liapunov stability theory, performing stability demonstration on the motor position servo system, and obtaining a global asymptotic stability result of the system by operatinga Barbalat lemma. The motor position servo system self-adaptive control method based on an interference observer is based on an integration series model and the interference observer of the motor position servo system, designs a non-linear control method based on the interference observer, integrates the non-linear control method with self-adaptive control, respectively estimates unmodeled interference and parameter nondeterminacy to enable the servo system to achieve the effect of global asymptotic stability when unmodeled interference is time-varying interference for the servo system, and solves the strong parameter nondeterminacy problem and the strong nondeterminacy non-linear problem of the system so as to enable the system to obtain better tracking performance.

This disclosure relates to transporting goods using a fleet of vehicles that is optimised. A processor solves a linear program to optimise a cost value by selecting one of multiple fleet configuration candidates comprising a number and type of vehicles that meet a transport demand at minimum cost. The linear program comprises constraints associated with multiple days. The processor then determines for one of the multiple days a further fleet configuration candidate based on an output of solving the linear problem and adds the further fleet configuration candidate to the multiple fleet configuration candidates by including an additional corresponding column into the linear program. The steps of solving the linear program, determining a further fleet configuration candidate and adding the further fleet configuration candidate to the multiple fleet candidates are then repeated until a termination condition is met.

The invention discloses a control method of a driving system of a permanent magnet synchronous motor of an electrical automobile considering iron loss, and provides a control method of a driving system of a permanent magnetic synchronous motor considering iron loss based on a self-adaptive fuzzy backstepping method, which solves the non-linear problem of the power driving and control system of the motor of the electrical automobile, enables the motor to quickly reach the stable running state and is more suitable for the control objects requiring quick dynamic response, such as the driving system of the electrical automobile. The control rules u[d] and u[q] only adopt one self-adaptive parameter theta, so as to reduce the calculation amount. The method has the advantages that the problem of position tracking and control of the permanent magnet synchronous motor considering the iron loss under the conditions of orienting to the site and having undetermined parameter and load torque disturbance is solved; the fuzzy logic system is used for approximating to the unknown non-linear item, and the self-adaptive fuzzy backstepping method is used for enabling the tracking error to approximate to 0; the more accurate control precision is reached, and the ideal position tracking and control effect is ensured.

The invention provides a thermal power generating unit operation optimization method and device based on consumption difference analysis. The method comprises the following steps: a thermal power generating unit working process model is established based on an improved least square support vector machine algorithm; improved particle swarm optimization is adopted for optimizing parametric variables affecting the net coal consumption rate in the thermal power generating unit working process model, and a global optimum affecting the net coal consumption rate is output; operation of a thermal power generating unit is guided according to parametric variable data corresponding to the global optimum so as to make the thermal power generating unit operate at the optimal net coal consumption rate. According to the thermal power generating unit operation optimization method and device based on consumption difference analysis, the modeling method of the improved least square support vector machine algorithm is used for converting the nonlinear problem of steam working in the thermal power generating unit into the linear problem in a high-dimensional plane, an optimal decision variable is obtained finally, the optimal decision variable is used for guiding the operation of the thermal power generating unit to make the thermal power generating unit operate at the optimal net coal consumption rate, and therefore the energy utilization rate and economic benefit of the thermal power generating unit are increased.

The invention discloses a modulator and a designing method thereof. The modulator comprises an analog filter, an analog adder, a multi-position quantizer, a digital loop filter, and a multi-position feedback digital-to-analog converter (DAC), wherein the analog filter is used for pre-modulating input analog signals, the analog adder is used for summing the analog signals, the multi-position quantizer is used for converting the sum of the analog signals into multi-position digital signals and outputting the multi-position digital signals, the digital loop filter is used for filtering the multi-position digital signals output by the multi-position quantizer, and the multi-position feedback digital-to-analog converter is used for converting the filtered multi-position digital signals into feedback analog signals. By the designing method disclosed by the invention, a stable modulator can be structured fast and conveniently; and as the digital loop filter is adopted to shape quantized noise and mismatched noise, the modulator not only has high stability, but also has good noise shaping capability, can effectively solve the non-linear problem of the multi-position feedback DAC, and can be used for high-speed and high-precision analog-to-digital conversion.

The present invention provides a touchpad module which obtains a touching sensibility and a uniform transmission of light to avoid non-linear problem by using a soft touch pad.

The invention relates to a low dispersion slope dispersion-shifted single-mode fiber for large capacity transmission comprising a core and a cladding. Said fiber is characterized in that said core has three to five core segments having different refractive index profiles, and said cladding has four to six cladding segments. The total dispersion slope of said fiber at 1550 nm is less than 0.060 ps/nm²·km, the zero dispersion wavelength is less than 1420 nm, the effective area ranges from 55 μm² to 65 μm², and the dispersion in the region of 1530 nm˜1565 nm ranges from 5.0 ps/nm²·km to 12.0 ps/nm²·km. The fiber has low dispersion slope, moderate dispersion, low attenuation, and excellent bend resistance performance. It is suitable for a high-speed (10 Gbits/s and 40 Gbits/s), large capacity, and long distance DWDM system. Therefore, not only the non-linear problem that fazes high-speed communication is solved effectively, but also the DWDM transmission at 10 Gbits/s can be realized within a wider wavelength range. In addition, low dispersion slope is advantageous for comprehensive management of dispersion, so that the requirement for long distance non-electric relay can be fulfilled.

The invention relates to a bituminous pavement structural analysis and increment method based on a modulus stress and strain dependence model of pavement materials. The method includes the steps of according to the structural pattern and material type of a bituminous pavement in a simulation analysis, determining the thickness and Poisson's ratio of each layer and the modulus stress and strain dependence model of the pavement materials, adopting the modulus stress and strain dependence model of the pavement materials to represent the modulus of each layer of a bituminous pavement structure, combining calculation load with interlayer combination conditions to create a calculation analysis system, using an increment method as an analysis basis, obtaining a modulus matrix of each point of theinteriors of pavement structural layers through finite element software numerical calculation, and based on the steps above, calculating the stress, strain and displacement of an arbitrary point in the bituminous pavement structure according to an elastic layered system theory. According to the method, influences caused by non-linear problems of materials on pavement mechanical calculation are taken into account to make the force analysis of the bituminous pavement structure more reasonable and complete.

The invention discloses an SFLA-SVM-based digital water island online agent adding control method. The method comprises the steps of obtaining an inflow monitoring index and determining a target function and a decision variable of an SFLA-SVM agent adding model; building an SVM model of the agent adding amount and the monitoring index; applying a chaos SFLA to the SVM model to obtain an optimal solution of each parameter; using the optimal solutions for learning training of the SVM model, and building the SFLA-SVM agent adding model; and inputting the detected inflow monitoring index into the SFLA-SVM agent adding model, and determining the optimal agent adding amount of a current time. The method overcomes bad effect on running process caused by time-varying characteristics of the water quality of inflow; the optimal agent adding amount is updated in real time, so that online control of agent adding process is achieved, waste of agent and labor and running cost are reduced, and the quality standard of outflow is satisfied; the calculation speed and the precision of the agent adding model are improved, so that local optical problem is avoided, non-linear problems are solved, and explanation and prediction capabilities of the model are enhanced.

The invention relates to an economic scheduling method for a micro-grid system. Based on the minimum operation cost as the control target, target functions and corresponding constraint conditions in three operation states of grid-connected operation, isolated-grid long-term stable operation, and isolated-grid short-term operation are respectively built, the built target functions cover device operation costs such as the device depreciation cost, the fuel cost, the maintenance cost, the start-stop cost, and the environmental protection cost etc. and various comprehensive cost influence factors such as the power purchase and selling cost, the load-shedding cost, and the line loss cost etc. via modeling of various devices in the system, non-linear problems are converted to linear problems by employing a sectional linearization processing method, decision variables such as 0 and 1 are introduced to convert quadratic constraint in the constraint to one-time constraint, and the solution is obtained in a time stratified manner. According to the method, various optional scheduling modes are provided, the applicability is high, the accuracy of calculating results is high, the calculating speed is fast, and the method can be applicable to large-scale micro-grid optimization scheduling.

The invention provides a bayesian estimation-based particle filter gravity-assisted inertial navigation matching method. When solving non-linear problems, particle filter prevents linearization-caused errors and solves the problem that the traditional point matching Sandia algorithm easily produces divergence in a large-gravity anomalous change matching area. Through use of inertial navigation position information as quantity of state, a gravimeter measured value as observed quantity, bayesian estimation-based particle filter, and a random sample average replacing a probability density function conditional mean, inertial navigation system state variable is estimated.

In object registration and recognition based on a set of known templates, the tremendous set of possible transformations that may relate the template and an observed signature makes any detection and recognition problem ill-defined unless this variability is taken into account. The present invention estimates the deformation that transforms some pre-chosen representation of an object (template) into the current observation. The method employs a set of non-linear operators to replace a high dimensional problem by an equivalent linear problem, expressed in terms of the unknown parameters of the transformation model. The solution is applicable to any homeomorphic transformation regardless of its magnitude. In the special case where the transformation is affine the solution is shown to be exact.

The invention relates to an operation time forecasting method of buses on road segments of bus lanes. According to the operation time forecasting method, through the learning process that input vectors are mapped to a high-dimensional space through a kernel function and a regression function is solved in the high-dimensional space, a nonlinear problem is converted to a linear problem, and forecasting precision of travel time of buses on the bus lanes is obviously improved; in addition, basic kernel functions are subjected to weighted addition to obtain a combined kernel function, characteristics of different kernel functions are maintained, different types of data inputs can be better processed, a model has higher robustness, the establishment process of smart traffic is promoted, and the method has far-reaching influence on optimal operation of bus systems on the bus lanes and outgoing convenience of passengers, and therefore the method can be widely applied to the field of operation time forecasting of the buses on the road segments of the bus lanes.

The invention provides a control method for a servo speed-regulation system with load acceleration feedback. First, motor angular speed feedback is extracted for speed ring calculation to obtain an angular accelerated speed instruction; then angular accelerated speed of a load is extracted, the angular rate of an orientation gyroscope is collected, and a current loop controlled quantity is calculated by the utilization of angular accelerated speed feedback; a current loop controlled quantity is calculated according to MTPA; line current is collected to calculate alternate and direct shaft current of a PMSM under dq coordinates; finally, a dq shaft voltage controlled quantity serves as input of park conversion of the PMSM to complete control over the motor. With the control method, influences on tracking precision of shooting impact force borne by a gun servo load tail end can be effectively restrained, positive effects on solving of the problem of structural resonance between a transmission system and the load in the gun servo system and a tooth space non-linear problem in a transmission chain are achieved, and then the performance of the gun servo system is improved.

The present invention discloses an electric power system transient stability analysis method. The electric power system transient stability analysis method mainly comprises a time domain simulation method and a direct method. A transient energy function method belongs to the direct method. The transient energy function method model is simple, considers the non-linear problem, can avoid complex numerical integration operation, is fast in computing speed and can provide system stability margin indexes, and the restriction of the model precision, critical point selectivity and linearity path hypothesis allows a traditional transient energy function to always have the conservation problem. The improved transient energy function method based on the SMR (Squared Matrix Representation) technology introduces the SMR technology to improve the transient energy function analysis method, a superposition program is employed to obtain the optimal Lyapunov function so as to improve the problem of a traditional transient energy function conservation.

The invention relates to a cross-linked core-shell structure nano polymer microsphere and a preparation method thereof, belonging to the technical field of polymer materials. The present invention uses a variety of organic olefin monomers as raw materials, and is prepared by emulsion or suspension polymerization with water as the medium under the condition of the presence of emulsifiers and initiators; the product has a core-shell structure, and both the inside of the core and the inside of the shell present Linked, the core and the shell are connected by chemical bonds, and the particle size is less than 100nm. In the present invention, by changing the composition and structure of the core and the shell, a variety of soft-core hard-shell or hard-core soft-shell nano-polymer microspheres with different physical and chemical properties are obtained, which has a high degree of freedom in the choice of structure design. The invention not only solves the problem that the core-shell polymer microspheres do not have a nanometer scale, but also solves the problem that the core and the shell are mostly linear polymers in the past, so that it has wider application prospects in the field of nanotechnology.

The invention discloses a two-time scanning-based high high-resolution optical scanning holographic section imaging method, belongs to the field of optical scanning and mainly overcomes the defect that larger defocus noise exists in the prior art when any two-dimensional sliced image is reconstructed. The two-time scanning-based high high-resolution optical scanning holographic section imaging method comprises the following steps of carrying out two-dimensional scanning on an object on a two-dimensional scanning mirror for the first time, moving the object towards the direction of the two-dimensional scanning mirror by a distance deltaZ after a first matrix equation containing section information is obtained and carrying out scanning on the object for the second time to obtain a second matrix equation containing the section information; and then integrating the first matrix equation and the second matrix equation into a minimum linear equation, converting the solution of a linear problem into a minimum problem and realizing section imaging through introducing a conjugate gradient algorithm. Through the technical scheme, the two-time scanning-based high high-resolution optical scanning holographic section imaging method has the beneficial effects that the high-precision section imaging is realized, and the defocus noise is greatly reduced. The two-time scanning-based high high-resolution optical scanning holographic section imaging method is suitable for various fields.

The invention discloses a resistance-changing-type single-fault-source diagnosing method for a mine ventilation system based on air volume characteristics. A training sample of the fault and air volume relation is generated through a mine ventilation simulating system (MVSS), a classification model and a regression model based on a support vector machine (SVM) are built, and the fault position andequivalent air resistance are diagnosed. The topology structure of a ventilation system network is complex, change of the air resistance of one of branches of the ventilation system network gives rise to change of the air volume of the branch and the ventilation network of a partial area, the air volume serves as a vector mode so as to distinguish the topology position where a resistance-changing-type fault occurs, and the single-fault-source SVM diagnosing method is put forward to diagnose the resistance-changing-type single fault source position and fault degree of the mine ventilation system; a final decision model is built according to the method, the method is simple, human interference is less, connection between data is objectively reflected, and the method is suitable for solvingthe essential non-linear problem; and the model is determined by a support vector, data dimension disaster is avoided, and good robustness is achieved.

A system that determines promotional pricing for a product and for an objective function receives a non-linear time-dependent optimization problem for the product, where the non-linear problem includes a demand model and a plurality of constraints, and the constraints include a price ladder that includes a plurality of time periods and a non-promotional price for the product at each time period. For each of the time periods, the system determines a change in the objective function when the price at that time period includes a promotional price and all other prices on the price ladder are set to the non-promotional price to generate coefficients. The system determines a maximum value of the coefficients at each time period, and generates an approximate Mixed Integer Programming (“MIP”) problem based on the coefficients. The system determines a Linear Programming (“LP”) relaxation of the MIP problem, and solves the LP relaxation.

The invention discloses a road black spot linear cause analysis method based on binary Logistic regression, and the method comprises the following steps: 1, dividing a road to be researched into n road segment units according to the length; 2, analyzing the safety of each road segment unit, and determining road segments with the lower safety as black spots; 3, classifying the traffic accidents happening at each black spot into K classes according to the types of accidents, and converting the number of various types of accidents happening at the road segment units into a binary variable; 4, selecting Z types of linear indexes for describing the linear features of each black spot unit; 5, analyzing the impact on the occurrence of different types of accidents from various linear indexes of the black spots through a binary Logistic regression model. The method can be used for determining the impact on various types of accidents from the linear features of the road, helps a road traffic safety administrative department find a linear problem of a block spot, and is of the instructive significance to the design and construction of a road in future.