[Algorithms] Solve Complex Problems in JavaScript with Dynamic Programming
Every dynamic programming algorithm starts with a grid. It entails solving subproblems and builds up to solving the big problem. Let’s break down a problem and solve it in pieces using dynamic programming with JavaScript.
/** * 給一個浮點數序列,取最大乘積連續子串的值,例如 -2.5,4,0,3,0.5,8,-1,則取出的最大乘積連續子串為3,0.5,8。也就是說,上述陣列中,3 0.5 8這3個數的乘積30.58=12是最大的,而且是連續的 * @param {*} a*/ function MaxProductSubstring (a) { let maxEnd = a[0] let maxRes = a[0] for (let i = 1; i < a.length; i++) { maxEnd = Math.max(maxEnd * a[i], a[i]) maxRes = Math.max(maxRes, maxEnd) } return maxRes }
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