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1. Mean square error of single measurement and mean square error of arithmetic mean array = [ 120.0360 120.0390 120.0260 120.0270 120.0350 120.0360 120.0310 120.0250 119.9830 120.0410]; average = mean(array); r = array - average; error1 = (sum(r.^2)/(size(array,1)-1))^(1/2);%Mean square error of single measurement error2 = ...

catalogue 1 important knowledge points 1.1 genetic algorithm 1.2 quantum computing 1.3 quantum genetic algorithm 2. Operation steps 3 flow chart 4 quantum genetic algorithm -- Python implementation 4.1 data 4.2 code 4.3 results 5 quantum genetic algorithm -- Matlab implementation            ​ 1 important knowledge points In ...

1 Introduction A data classification model based on genetic algorithm and random forest. 1. The basic principle of random forest random forest was proposed by Leo Breiman(2001). It uses bootstrap resampling technology to repeatedly randomly select # b samples from the original training sample set # N # to generate a new training self-help sam ...

1, Introduction EMG is a method of recording the electrical activity of muscle at rest or contraction with electronic instruments, and examining the excitation and conduction function of nerve and muscle with electrical stimulation. EMG for short. Through this examination, the functional state of peripheral nerve, neuron, neuromuscular junctio ...

1, Introduction SIFT, scale invariant feature transformation, is a description used in the field of image processing. This description has scale invariance and can detect key points in the image. It is a local feature descriptor. 1. SIFT algorithm features: (1) It has good stability and invariance, can adapt to the changes of rotation, scale s ...

1, Introduction 1 Retinex 1.1 theory Retinex theory began with a series of contributions made by land and McCann in the 1960s. Its basic idea is that the color and brightness of a point perceived by human beings are not only determined by the absolute light entering the human eye, but also related to the color and brightness around it. Retinex ...

1, Introduction 1 concept of particle swarm optimization algorithm Particle swarm optimization (PSO) is an evolutionary computing technology. From the study of predation behavior of birds. The basic idea of particle swarm optimization algorithm is to find the optimal solution through the cooperation and information sharing among individuals in ...

1, Introduction 1 Overview BP (Back Propagation) neural network was proposed by the scientific research group headed by Rumelhart and McCelland in 1986. See their paper learning representations by Back Propagation errors published in Nature. BP neural network is a multilayer feedforward network trained by error back propagation algorithm. It ...

catalogue Dynamic regular expression brief introduction Dynamic matching expression - (?? expr) Modify the command matching the expression - (? @ cmd) Functional requirements of (@ cmd) Override command in expression - ${cmd} Dynamic regular expression brief introduction In a dynamic expression, you can require regexp to match. The ...

catalogue First, Simulated annealing algorithm (SA). 1. Basic theory of SA 2.SA solves the maximum value of the function 3.SA toolbox 2, Genetic algorithm (GA) 1. Theoretical basis of GA 2.GA solves the maximum value of function 3.GA toolbox 3, Particle swarm optimization (PSO) 1. Knowledge of PSO algorithm 2.PSO algorithm design 3. ...