【苦难coc】详细的暴击率调节步骤
主贴:【苦难COC】总伤15艺冰矛999万/根POB完全公开-流放之路 - 爱游戏,爱17173! http://bbs.17173.com/thread-11277367-1-1.html内含各种价位pob,
1、需要用到POB
首先随便找一个你身上+命中的 装备珠宝啥的 双击 编辑把命中写无限大
2、
脆弱从1开始往上一点一点加
3、观察【计算】面板中 旋风斩的暴击率构成列表,注意看最下边的那个7就是脆弱效果,然后看上边是不是接近100%,
重复步骤2 直到你暴击接近100%(切记命中如果99%,暴击率最高99%,暴击率不会超过命中,图中我的命中没有100%,所以上一步让你把命中无限编辑大,为了保证暴击率调试的准确性)
4、以上计算完毕后:
假如需要7脆弱。
5、代入元素异常公式(通常我们用西鲁斯8觉为基准,8900万生命,阙值大概是2500万-3000万《30-35%傻傻分不清》)
【脆弱】元素异常效果=25*(击中伤害/阙值(门槛)^0.4
7=25*(击中伤害/阙值(门槛)^0.4
这里需要注意“^”符号是次方的意思。就是你中学学的那个2的右上角带个小2 后边算完最后跟25相乘
(击中伤害/阙值(门槛)^0.4=7/25
(击中伤害/阙值(门槛)^0.4=0.28
(击中伤害/阙值(门槛)的0.4次方=0.28
这里反求比较复杂,给大家推荐一个工具,百度{次方计算器}
由于反求复杂,没有计算器。所以我们可以N次方写0.4.。。。填写【底数】看【连分数】此时连分数0.284最后一位不满5清零。=0.28
此时的底数是0.043(击中伤害/阙值肯定是小数【0.**】这样的,所以不要填什么几十几百,)
也就是
击中伤害/阙值=0.043
阙值是已知的2500万
25000000*0.043=1075000
107万
记住这个数值
看你的技能(看哪一个?一个一个看,武器上衣服上都看一下 哪一个伤害高 以哪一个为准)
这里不一定看冰矛。由于玩法不同,我的是冰矛伤害最高,你们可以找自己冰伤害最高的技能看这里的平均击中
1、如果大于107万,恭喜你 你可以达成满暴击
2、如果你伤害低与107万,那么你就要在衣服把【电光寒霜】换成【寒冰但/冰霜脉冲】辅助技能不能带【元素集中】,以此来过度到后期。这两个技能单次击中伤害非常高,轻松达成7以上脆弱
3、一个中型暴击率星团洗出来【暴风之眼40%非伤害型异常提高】假设你触发5脆弱此时就变成5*(1+40%)=6
4、其实你依然可以满暴击。只不过延迟严重,为什么?因为【直供要害5%概率双倍伤害*2颗=10%,永恒珠宝洗出5% 总共15%】
也就是你会发生平均击中翻倍的情况,那么你肯定可以达成7脆弱,
【低配】我们衣服每秒投射物6*7+7*7=91投射物 /1秒
15%概率 理论来说1秒会有91*0.15=14次是双倍伤害,
此时也能满爆,只是延迟比较严重 毕竟概率只有15%,需要宝钻药剂的加持即【可丝滑手感】
后期装备珠宝好了伤害上去了,宝钻换信仰伤害再次提升,
5、如果是药侠 100药剂效果。那么你平均击中几十万带个宝钻依然丝滑顺畅
总结 造价不到50E即可西鲁斯秒阶段,各种图各种秒,T20,会多技能,也过了。不追求极限的话,这50E你就毕业了。就这么简单
最后 推荐攻速2档 14-15.15之间
如果鞋子有提速就 13-14攻速
鞋子没有提速 就14-15.15之间
最后最后,如果你暴击率满
回去把命中回复到正常值,然后脆弱写15(满暴击情况下脆弱写多少都无所谓了哪怕你写100000000),
开始你的POB 跑装备、珠宝,进行造车设计,并且注意你的命中,要想办法堆到97%以上,这个值以上攻击失败的效果我们是无法体会到的。 最后照着POB买装备/做装备
本帖最后由 6544321吃饭 于 2021-6-24 09:34 编辑
{:3104:}字都认识,按凑一起就看不大懂了 技术贴,不明觉厉 {:3112:} 我觉得楼主想说的是 阈 值。
我觉得楼主想说的是 阈 值。
对 是的 带了元素集中,无法造成脆弱。 暴风之眼只有20%异常吧 可以很细节 学*了 好复杂,老湿,最后没总结吗? 现在是2022了吗?
好复杂,学*了 挺好的 正确态度
而不是像有些人张口就来 大概明白了,就是对于这么个方程
data:image/png;base64,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*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*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
其中n是需要的脆弱层数,x是主攻技能的击中伤害(单位是万)
如果基础爆和inc不够造成n比较高,那么x就会随之变高
可以选择
[*]堆爆击,或者下掉元素击中,把n压下去
[*]堆伤害,把x抬起来
[*]找异常伤害加成,让n更容易达成
本帖最后由 吉姆刘 于 2021-6-23 15:05 编辑
吉姆刘 发表于 2021-6-23 14:40
大概明白了,就是对于这么个方程
此处有掌声 吉姆刘 发表于 2021-6-23 14:40
大概明白了,就是对于这么个方程
第三个有点问题,元素异常提高是让(25*n)*一个系数,用你的话说就是,让最终实际效果超出对应伤害得效果 爽是很爽。就是容易挂
页:
[1]