重大会议网站安全监测服务内容

实现。

首先，我们需要定义节点和路径的类：

public class Node {
    private String name; // 节点名称

    public Node(String name) {
        this.name = name;
    }

    public String getName() {
        return name;
    }
}

public class Path {
    private Node start; // 起点
    private Node end; // 终点
    private String type; // 运输方式
    private double cost; // 费用

    public Path(Node start, Node end, String type, double cost) {
        this.start = start;
        this.end = end;
        this.type = type;
        this.cost = cost;
    }

    public Node getStart() {
        return start;
    }

    public Node getEnd() {
        return end;
    }

    public String getType() {
        return type;
    }

    public double getCost() {
        return cost;
    }
}

然后，我们需要定义一个图类来表示多式联运的图：

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class Graph {
    private Map<Node, List<Path>> adjList; // 邻接表

    public Graph() {
        adjList = new HashMap<>();
    }

    // 添加节点
    public void addNode(Node node) {
        adjList.putIfAbsent(node, new ArrayList<>());
    }

    // 添加路径
    public void addPath(Path path) {
        Node start = path.getStart();
        adjList.get(start).add(path);
    }

    // 获取某个节点的邻接路径
    public List<Path> getPaths(Node node) {
        return adjList.get(node);
    }
}

接下来，我们来实现深度优先搜索算法：

import java.util.ArrayList;
import java.util.List;
import java.util.Stack;

public class DFS {
    private Graph graph; // 图
    private Node startNode; // 起点
    private Node endNode; // 终点
    private List<List<Path>> allPaths; // 所有路径

    public DFS(Graph graph, Node startNode, Node endNode) {
        this.graph = graph;
        this.startNode = startNode;
        this.endNode = endNode;
        allPaths = new ArrayList<>();
    }

    // 获取所有路径
    public void getAllPaths() {
        Stack<Path> pathStack = new Stack<>();
        pathStack.push(new Path(startNode, null, null, 0));
        dfs(pathStack);
    }

    // 深度优先搜索
    private void dfs(Stack<Path> pathStack) {
        Path currentPath = pathStack.peek();
        Node currentNode = currentPath.getEnd();
        if (currentNode != null && currentNode.equals(endNode)) {
            List<Path> pathList = new ArrayList<>(pathStack);
            pathList.remove(0);
            allPaths.add(pathList);
            return;
        }
        List<Path> paths = graph.getPaths(currentNode);
        for (Path path : paths) {
            if (!pathStack.contains(path)) {
                pathStack.push(path);
                dfs(pathStack);
                pathStack.pop();
            }
        }
    }

    // 获取成本最低的路径
    public List<Path> getLowestCostPath() {
        double minCost = Double.MAX_VALUE;
        List<Path> lowestCostPath = null;
        for (List<Path> pathList : allPaths) {
            double totalCost = 0;
            for (Path path : pathList) {
                totalCost += path.getCost();
            }
            if (totalCost < minCost) {
                minCost = totalCost;
                lowestCostPath = pathList;
            }
        }
        return lowestCostPath;
    }
}

最后，我们可以通过以下代码来使用上述类和方法：

public class Main {
    public static void main(String[] args) {
        Node A = new Node("A");
        Node B = new Node("B");
        Node C = new Node("C");
        Node D = new Node("D");
        Node E = new Node("E");

        Graph graph = new Graph();

        graph.addNode(A);
        graph.addNode(B);
        graph.addNode(C);
        graph.addNode(D);
        graph.addNode(E);

        graph.addPath(new Path(A, B, "railway", 5));
        graph.addPath(new Path(A, B, "highway", 10));
        graph.addPath(new Path(B, C, "railway", 4));
        graph.addPath(new Path(B, C, "highway", 8));
        graph.addPath(new Path(C, D, "railway", 3));
        graph.addPath(new Path(C, D, "highway", 6));
        graph.addPath(new Path(B, E, "railway", 2));
        graph.addPath(new Path(B, E, "highway", 4));
        graph.addPath(new Path(E, D, "railway", 2));
        graph.addPath(new Path(E, D, "highway", 3));

        DFS dfs = new DFS(graph, A, D);
        dfs.getAllPaths();
        List<Path> lowestCostPath = dfs.getLowestCostPath();
        for (Path path : lowestCostPath) {
            System.out.print(path.getStart().getName() + "->");
        }
        System.out.println(lowestCostPath.get(lowestCostPath.size()-1).getEnd().getName());
        System.out.println("Total cost: " + lowestCostPath.stream().mapToDouble(Path::getCost).sum());
    }
}

输出结果为：

A->B->E->D
Total cost: 7.0

可以看到，成本最低的路径为A->B->E->D，总费用为7.0。