C++ 框架赋能嵌入式系统智能决策制定

#include <boost/hana/tuple.hpp>
#include <boost/hana/fold_left.hpp>

// 专家系统规则
constexpr auto rules = boost::hana::make_tuple(
    boost::hana::make_pair("temp < 20", "turn on heater"),
    boost::hana::make_pair("temp > 30", "turn on AC")
);

int main() {
    // 输入传感器数据
    auto temp = 25;
    
    // 根据规则生成决策
    auto decision = boost::hana::fold_left(rules, [](auto acc, auto rule) {
        auto condition = boost::hana::first(rule);
        auto action = boost::hana::second(rule);
        return boost::hana::if_(condition(temp), action, acc);
    }, "");

    // 执行决策
    std::cout << "Decision: " << decision << std::endl;
}

#include <Eigen/Dense>

int main() {
    // 决策变量和系数
    Eigen::VectorXf x(2);
    x << 1, 2;
    Eigen::MatrixXf A(2, 2);
    A << 1, 2,
         3, 4;

    // 线性方程组求解
    Eigen::VectorXf b = {5, 7};
    x = A.ldlt().solve(b);

    // 基于决策变量进行决策
    std::cout << "Decision: " << x << std::endl;
}

#include <cuda_runtime.h>

// GPU 函数
__global__ void kernel(float* d_data, cudaStream_t stream) {
    int i = blockIdx.x * blockDim.x + threadIdx.x;
    // ... 进行决策计算 ...
}

int main() {
    // 分配 GPU 内存
    float* d_data;
    cudaMalloc(&d_data, size);

    // 创建并行流
    cudaStream_t stream;
    cudaStreamCreate(&stream);

    // 启动 GPU 内核
    kernel<<<gridDim, blockDim, 0, stream>>>(d_data, stream);
    
    // 同步流
    cudaStreamSynchronize(stream);
}