6 results about "Multivariate optimization" patented technology

This invention relates to the field of optical communication, providing a method, system, device, product, and medium for optimizing the energy efficiency of multi-access point optical communication. The method includes: calculating the link channel gain to obtain the composite channel gain; obtaining the received energy at the receiver; establishing a nonlinear received energy expression based on the received energy; constructing a battery dynamics model using the nonlinear received energy expression to obtain device energy constraints; establishing a arrival Markov matrix and a service Markov matrix based on the number of participating communication devices and their obstruction states; calculating the arrival martingale and service martingale; calculating the queue length change based on the arrival martingale and service martingale; establishing a delay default probability inequality through the queue length change to obtain an upper bound on the delay default probability; establishing communication optimization constraints; constructing a multivariate optimization equation; solving the multivariate optimization equation based on the communication optimization constraints to obtain communication optimization parameters; and optimizing the optical communication using these communication optimization parameters.

The invention belongs to the technical field of air compressors, and provides an air compressor station intelligent group control energy-saving system based on multi-machine linkage, which comprises a data acquisition unit, a central control unit and an execution regulation and control unit, the data acquisition unit is used for acquiring operation state parameters and environment working condition parameters of all air compressors in an air compressor station and load demand parameters of a gas using end in real time. The central control unit integrates a load prediction module, an energy efficiency evaluation module, a group control scheduling module, an equipment health monitoring module and an energy efficiency optimization feedback module, realizes minimum energy consumption scheduling under cooperative operation of multiple air compressors through high-precision sensing, dynamic modeling and multivariable optimization, has equipment abnormity early warning and model self-correction capabilities, and is high in reliability and high in reliability. Therefore, the system energy consumption can be obviously reduced, and the gas supply stability and the intelligent level are improved.

The invention discloses a dynamic proportion control system and method in a prebiotic production process, relates to the technical field of production process control, and continuously reflects actual states of a raw material component proportion Red, a fermentation tank temperature Tem, a pH value Phv, a dissolved oxygen content Oxy and a flora metabolism rate Met in a current batch based on a real-time production state set Sta. Linkage adjustment is carried out on production parameters through a multivariable optimization input index set Inp and a current optimal dynamic matching strategy Opt, so that parameter changes in the production process are not mutually-separated local repair any more, but overall cooperative control is carried out around the same target; in this way, the problems that in the prior art, a fixed proportion is difficult to adapt to raw material batch fluctuation, parameter changes in the fermentation process cannot be responded in time, and finally the product quality and the output efficiency are unstable can be directly solved. And meanwhile, a closed-loop control state set Clo is formed in combination with a feedback signal Fbk in the execution process to continue correction.

The invention discloses a privacy-protected multi-cell wireless distributed AI method and device, and the method comprises the steps: in a multi-base-station federated learning system, edge equipment participates in a federated learning process through being connected to base stations and communicating with the base stations, and the edge equipment adds noise in an uploaded model to apply a differential privacy strategy. The privacy leakage of all edge devices in the system can be minimized by jointly adjusting the connection distribution between the edge device base stations, the edge device transmitting power and the difference privacy noise added by the edge devices in the model. A multivariable optimization problem about edge device allocation, transmitting power and differential privacy noise standard deviation, which minimizes overall privacy leakage, is provided, and an iterative alternative optimization algorithm is used. And solving the edge device connection allocation optimization sub-problem, the transmitting power optimization sub-problem and the privacy noise optimization sub-problem in turn to obtain a suboptimal solution of the multivariate optimization problem.

This invention discloses an intelligent control method and system for PEM electrolyzers, relating to the field of new energy technology. Addressing the problems of existing PEM electrolyzers under fluctuating operating conditions, such as difficulty in dynamically coordinating multiple physical fields, difficulty in sensing internal states, and the inability to balance operating efficiency and equipment lifespan, this invention proposes a multivariate collaborative optimization control based on the Electrolysis Process State Function (EPSF). By calculating the proton conduction efficiency function and the catalytic activity distribution optimization function in real time, the key internal states of the electrolyzer are accurately quantified. Furthermore, a multivariate optimization objective function integrating efficiency and degradation cost is constructed and solved to obtain optimal control parameters such as current density and pressure online. A multi-timescale rolling optimization architecture and a parameter online identification algorithm with a forgetting factor are further introduced to achieve synergy between rapid response, efficiency optimization, and lifespan management. This invention significantly improves the operating efficiency, stability, and durability of PEM electrolyzers under dynamic loads.

This invention discloses a method for optimizing the number of molecules released in a multi-input multi-output (MIMO) molecular communication system. The method includes: acquiring simulation data and establishing a time-varying channel impulse response function (TMR); minimizing the error between the predicted value of the TMR and the simulation data using a nonlinear fitting method to obtain a well-fitted TMR; deriving the average bit error rate (BER) of the MIMO system in the m-th time slot based on the fitted TMR, and establishing a multivariate optimization objective function for the current time slot; establishing and training a deep neural network; and inputting the initial distance vectors formed by each link into the trained deep neural network to obtain the optimal molecule release number vector for each sending nanomachine. This method can optimize the number of molecules released by the sending nanomachines in less time and with lower computational complexity, significantly reducing the average BER.