[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reports-detail-2026-10-02-ai-performance-zh-TW":3,"reports-algorithms":40},{"slug":4,"type":5,"extremeSubtype":6,"publishAt":7,"updateTime":8,"coverImage":9,"viewCount":10,"title":11,"metaTitle":12,"metaDesc":13,"summary":14,"content":15,"readMinutes":16,"related":17},"2026-10-02-ai-performance","daily",null,"2026-10-03 00:30:00","2026-10-03 00:32:07","\u002Fstatic\u002Fog\u002F2026-10-02-ai-performance.jpg",0,"AI 演算法高低分對比，命中率揭曉","加拿大28 AI 演算法表現揭曉，命中率一覽","2026年10月2日，加拿大28 AI 演算法表現出色與黯淡並存。新晉黑馬「局部熵」演算法以46.63%領跑，而「遺漏遞減」僅34.04%。","昨日AI演算法表現分化，「局部熵」演算法穩居首位，精準率達46.63%；而「遺漏遞減」演算法則表現令人遺憾，僅34.04%。","## 昨日 AI 演算法表現引發關注\n\n在 2026 年 10 月 2 日的加拿大28統計中，共進行了 402 期的開獎，其中 AI 演算法的表現成為本次分析的焦點。我們分別從高分榜單和低分榜單入手，帶大家解析。**首要關注點在於，局部熵演算法的強勢表現，以及部分演算法低迷的狀態。**\n\n### 高分榜單解析\n\n我們首先看向排名前五的演算法。**局部熵演算法以綜合命中率 46.63% 高居榜首**，其在號碼預測的命中率更是達到了 58.6%。緊隨其後的是凱利公式和隨機森林，它們的綜合命中率分別為 46.63% 和 46.33%。這三套演算法不僅在整體表現上領先，更在多個子項中表現優異。\n\n此外，深度學習和深度神經網路演算法分列第四和第五，綜合命中率分別為 46.26% 和 45.51%。這說明在昨日的資料中，基於深度學習模型的演算法依然保持了穩定的發揮。\n\n### 低分榜單揭示\n\n接下來，我們再看看低分榜單。排名倒數的演算法包括遺漏追逐、遺漏遞減以及雙步躍遷。**遺漏遞減演算法的綜合命中率為 34.04%，僅為高分演算法的一半左右**。這種表現可能說明這些模型在當前特定資料形態下，未能準確捕捉到關鍵的統計特徵。\n\n### 資料趨勢和背後邏輯\n\n與之匹配的，是當日的資料分佈。例如，在跨度分佈中，跨度為 5 的資料點最多，達 62 次，再加上大小比和單雙比的平均偏差（分別為 47.76% 和 52.24%），這種情況可能更適合高分演算法的預測機制，而這些低分演算法在應對偏態時略顯不足。\n\n### 極端事件點睛\n\n昨日還出現了兩起極端豹子號事件和罕見總和值為 0 的結果。這些事件雖屬高機率之外，但也為演算法校驗提供了特殊場景的有力基礎。\n\n### 總結和展望\n\n透過以上分析，我們發現，每種演算法表現的背後都與其對應的資料特性密切相關。對於玩家或研究者來說，選擇適合當前資料表現的演算法，是提升命中率的重要因素。接下來，我們會持續觀察這些演算法的表現，期待在不同的資料形態下看到它們的亮點與突破。",3,[18,27,34],{"slug":19,"type":20,"extremeSubtype":21,"publishAt":22,"coverImage":23,"viewCount":10,"title":24,"summary":25,"readMinutes":26},"2026-10-12-extreme-sum-zero","extreme","E2","2026-10-12 15:23:26","\u002Fstatic\u002Fog\u002F2026-10-12-extreme-sum-zero.jpg","罕見事件：加拿大28和值跌至0","加拿大28第3493115期出現罕見和值0，僅有0.1%的機率，上次發生距現在已有一天。",1,{"slug":28,"type":20,"extremeSubtype":29,"publishAt":30,"coverImage":31,"viewCount":10,"title":32,"summary":33,"readMinutes":26},"2026-10-12-extreme-triple-zero","E1","2026-10-12 15:23:15","\u002Fstatic\u002Fog\u002F2026-10-12-extreme-triple-zero.jpg","加拿大28豹子號000現身，機率僅1%","第3493115期加拿大28開出豹子號000，極端事件機率低至1%，罕見現象再度出現。",{"slug":35,"type":20,"extremeSubtype":29,"publishAt":36,"coverImage":37,"viewCount":10,"title":38,"summary":39,"readMinutes":26},"2026-10-12-extreme-triple-three","2026-10-12 06:38:20","\u002Fstatic\u002Fog\u002F2026-10-12-extreme-triple-three.jpg","加拿大28豹子號333現身，機率僅1%","第3492965期加拿大28開獎竟爆出豹子號333，驚喜機率僅1%。",[41,46,52,57,63,69,75,81,87,93,99,105,111,117,123,129,135,141,146,152,158,164,170,176,182,188,194,200,206,212],{"code":42,"nameZhCn":43,"nameZhTw":44,"nameEnUs":45,"sortOrder":26},"quantum_probability","量子概率引擎","量子機率引擎","Quantum Probability Engine",{"code":47,"nameZhCn":48,"nameZhTw":49,"nameEnUs":50,"sortOrder":51},"deep_neural_network","深度神经网络","深度神經網路","Deep Neural Network",2,{"code":53,"nameZhCn":54,"nameZhTw":55,"nameEnUs":56,"sortOrder":16},"genetic_evolution","遗传进化算法","遺傳進化演算法","Genetic Evolution Algorithm",{"code":58,"nameZhCn":59,"nameZhTw":60,"nameEnUs":61,"sortOrder":62},"markov_chain","马尔可夫链","馬可夫鏈","Markov Chain",4,{"code":64,"nameZhCn":65,"nameZhTw":66,"nameEnUs":67,"sortOrder":68},"deep_learning","深度学习","深度學習","Deep Learning",5,{"code":70,"nameZhCn":71,"nameZhTw":72,"nameEnUs":73,"sortOrder":74},"bayesian","贝叶斯推理","貝氏推論","Bayesian Inference",6,{"code":76,"nameZhCn":77,"nameZhTw":78,"nameEnUs":79,"sortOrder":80},"random_forest","随机森林","隨機森林","Random Forest",7,{"code":82,"nameZhCn":83,"nameZhTw":84,"nameEnUs":85,"sortOrder":86},"lstm","LSTM 长短期记忆","LSTM 長短期記憶","LSTM Network",8,{"code":88,"nameZhCn":89,"nameZhTw":90,"nameEnUs":91,"sortOrder":92},"monte_carlo","蒙特卡洛模拟","蒙地卡羅模擬","Monte Carlo Simulation",9,{"code":94,"nameZhCn":95,"nameZhTw":96,"nameEnUs":97,"sortOrder":98},"clustering","聚类追踪","聚類追蹤","Cluster Tracking",10,{"code":100,"nameZhCn":101,"nameZhTw":102,"nameEnUs":103,"sortOrder":104},"volatility","波动率","波動率","Volatility",11,{"code":106,"nameZhCn":107,"nameZhTw":108,"nameEnUs":109,"sortOrder":110},"edge_value","边缘值","邊緣值","Edge Value",12,{"code":112,"nameZhCn":113,"nameZhTw":114,"nameEnUs":115,"sortOrder":116},"anti_martingale","反马丁格尔","反馬丁格爾","Anti-Martingale",13,{"code":118,"nameZhCn":119,"nameZhTw":120,"nameEnUs":121,"sortOrder":122},"ensemble_voting","综合投票","綜合投票","Ensemble Voting",14,{"code":124,"nameZhCn":125,"nameZhTw":126,"nameEnUs":127,"sortOrder":128},"momentum","动量加速度","動量加速度","Momentum",15,{"code":130,"nameZhCn":131,"nameZhTw":132,"nameEnUs":133,"sortOrder":134},"quantile","分位数","分位數","Quantile",16,{"code":136,"nameZhCn":137,"nameZhTw":138,"nameEnUs":139,"sortOrder":140},"double_step_transition","双步转移","雙步轉移","Double-Step Transition",17,{"code":142,"nameZhCn":143,"nameZhTw":143,"nameEnUs":144,"sortOrder":145},"local_entropy","局部熵","Local Entropy",18,{"code":147,"nameZhCn":148,"nameZhTw":149,"nameEnUs":150,"sortOrder":151},"residual_trend","残差趋势","殘差趨勢","Residual Trend",19,{"code":153,"nameZhCn":154,"nameZhTw":155,"nameEnUs":156,"sortOrder":157},"streak_length","连势长度","連勢長度","Streak Length",20,{"code":159,"nameZhCn":160,"nameZhTw":161,"nameEnUs":162,"sortOrder":163},"decay_missing","衰减遗漏","衰減遺漏","Decay Missing",21,{"code":165,"nameZhCn":166,"nameZhTw":167,"nameEnUs":168,"sortOrder":169},"rule_voting","规则投票","規則投票","Rule Voting",22,{"code":171,"nameZhCn":172,"nameZhTw":173,"nameEnUs":174,"sortOrder":175},"cold_hot_balance","冷热平衡","冷熱平衡","Cold-Hot Balance",23,{"code":177,"nameZhCn":178,"nameZhTw":179,"nameEnUs":180,"sortOrder":181},"kelly","凯利公式","凱利公式","Kelly Criterion",24,{"code":183,"nameZhCn":184,"nameZhTw":185,"nameEnUs":186,"sortOrder":187},"mean_reversion","均值回归","均值回歸","Mean Reversion",25,{"code":189,"nameZhCn":190,"nameZhTw":191,"nameEnUs":192,"sortOrder":193},"autocorrelation","自相关","自相關","Autocorrelation",26,{"code":195,"nameZhCn":196,"nameZhTw":197,"nameEnUs":198,"sortOrder":199},"fibonacci","斐波那契","費波那契","Fibonacci",27,{"code":201,"nameZhCn":202,"nameZhTw":203,"nameEnUs":204,"sortOrder":205},"miss_chase","遗漏追热","遺漏追熱","Miss Chase",28,{"code":207,"nameZhCn":208,"nameZhTw":209,"nameEnUs":210,"sortOrder":211},"number_combination","数字组合","數字組合","Number Combination",29,{"code":213,"nameZhCn":214,"nameZhTw":215,"nameEnUs":216,"sortOrder":217},"recent_chain","近链推演","近鏈推演","Recent Chain",30]