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用JACOBI迭代法求解线性代数方程组，此迭代法是数值计算基本方法之一。(Use JACOBI iterative method for solving linear algebraic equations, and this iteration method is one of the basic method of numerical calculation.)

maple的入门级教程，maple的计算相比matlab更加简单也更容易上手(The entry-level tutorial maple, maple computing matlab simpler and easier to use compared to)

实现了QPSK在瑞利信道下的性能仿真,仿真结果与理论曲线相比较，结果相符。供大家参考。(It achieved the simulation of QPSK performance in Rayleigh channel.)

米散射相函数对比，包括散射相函数抽样，不同波长，不同折射率(The contrast of the phase function of the rice scattering, including the scattering phase function sampling, the different wavelengths and the different refractive index)

读取压缩包中类似格式的txt文件绘制扇形包络图(Read txt file compression format similar to drawing package envelope fan)

IEEE30节点遗传算法，简单实用，适合初学者学习，可用于配电网重构(Genetic algorithms, simple and practical, suitable for beginners to learn, can be used for distribution network reconfiguration)

对libsvm产生的model进行转换，从原先matlab的mat格式，转换为c语言的文本格式，然后进行预测预测(Allow phonetic typing Libsvm the model converted from the original Matlab mat format, converted to text format c language, and then to predict the forecast)

用matlab对chirp信号进行了仿真，表现出了chirp信号的frft变换积聚效果(Chirp signal using matlab simulation, the performance of the chirp signal frft transform accumulation effect)

评价图形的MSE,SNR，PSNR的GUI。(A　GUI　to evaluate the image s MSE,SNR and PSNR.)

针对粒子群优化算法应用于约束优化问题时易陷入局部极小值的问题, 提出了一种改进的粒子群优化算 法. 该算法综合了约束优化问题的目标函数值和约束函数的违反度值作为粒子群优化算法的双适应度值, 采用了 双适应值动态判断粒子群优化算法中粒子的优劣. 违反度值的计算引入了自适应加权系数, 相应地提出了调整各 权系数的自适应策略, 并改进了粒子群优化算法的粒子竞争选择策略, 拓展了粒子群优化算法的单适应值的应用 范围.应用约束自适应粒子群优化算法实现了城市水厂的节能优化调度. 结果表明, 该算法收敛速度快且结果可 靠. 粒子群优化算法为解决工程约束优化问题提供了一条可行途径(Considering that theparticleswarmoptimization( PSO) algorithmcanbeeasily trappedinto the local minimal valueinconstrainedoptimizationproblems, amodifiedconstrainedparticleswarmoptimiza
tionalgorithmwasproposed. Theobjective functionvalue andthe violationvalue of constraint functions wereeffectively combinedto formtwofitnesses, andthefitnesseswereadoptedto estimate if theparticle wassuperior or not ina dynamicway. Theadaptiveweight functionwasadoptedinthe calculationof the violationvalue. The strategy of keeping anadaptive relationof weight coefficientswasproposed, andthe strategyof swarmtournament selectionwasimproved. Theapplicationlocalizationsof thesinglefitnessof PSOwerewidenedaswell. ThemodifiedconstrainedPSOalgorithmwasappliedtosolveenergyoptimiza
tionproblemsof theurbanwater supplyprocess, whichshowedthat theconvergent speedof thealgorithm isfast andthe result isvalid. Afeasibleapproachto solvetheindustrial constraint optimizationproblems withPSOwasprovided.)