[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reports-detail-2026-10-04-week-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},"2026-10-04-week-ai-performance","weekly",null,"2026-10-05 00:35:00","2026-10-05 00:35:22","\u002Fstatic\u002Fog\u002F2026-10-04-week-ai-performance.jpg",0,"本週加拿大28極端事件與AI表現","加拿大28本週資料：極端事件與AI演算法表現","回顧本週加拿大28資料，觀察極端事件頻發及AI演算法表現亮點，深度解析資料中的關鍵趨勢與偏離。","加拿大28本週資料回顧，極端事件頻發，多次出現豹子號及和值為0，AI演算法中「局部熵」與「凱利公式」表現亮眼，命中率領先全局。","## 極端事件高頻現身\n\n本週加拿大28資料中，極端事件的出現頻率令人矚目。10月1日至10月4日期間，共發生了13起極端事件，其中包括多次罕見的豹子號，例如豹子號「888」在10月4日早間再次現身。此外，和值為0的局面亦在10月1日和10月2日先後呈現，這種情況在歷史資料中極為罕見，成為玩家熱議的焦點。\n\n統計顯示，10月1日的豹子號事件集中爆發，出現了「000」、「777」及「888」等多組罕見組合。當日資料的這種異常波動是否會延續，仍需觀察。\n\n## 大小單雙比波動解析\n\n從當週資料統計來看，總大小比維持在50.24%對49.76%，單雙比為49.58%對50.42%，整體接近平衡。然而，從每日波動可見，9月30日大號比例達到一週最高的50.87%，而10月2日則降至47.76%。這種差異顯示出大盤的隨機性較高，難以被預測。\n\n### 每日分佈對比\n\n| 日期       | 總期數 | 大號比例 | 單號比例 |\n|------------|--------|----------|----------|\n| 2026-09-28 | 403    | 50.37%   | 48.88%   |\n| 2026-09-29 | 309    | 50.16%   | 52.10%   |\n| 2026-09-30 | 403    | 50.87%   | 50.62%   |\n| 2026-10-01 | 402    | 48.76%   | 48.26%   |\n| 2026-10-02 | 402    | 47.76%   | 47.76%   |\n| 2026-10-03 | 402    | 53.73%   | 52.74%   |\n| 2026-10-04 | 402    | 50.00%   | 47.26%   |\n\n## AI演算法的頂級表現\n\n本週30套AI演算法中，「局部熵」以45.42%的綜合命中率與「凱利公式」並列第一，表現出色，尤其在號碼預測上分別達到了56.2%的高分。此外，「深度學習」演算法以45.21%的綜合準確率位列第三，與前兩者形成了競爭關係。\n\n與此同時，表現較差的演算法有「雙步躍遷」、「追失效」和「衰減遺漏」，其綜合準確率均低於36%，提示了優化空間。\n\n## 資料背後的思考\n\n很多人可能會認為，極端事件的高發提示了某種規律的存在。但真的是這樣嗎？從本週的資料分析來看，這些事件大多是隨機性的體現，而非某種預兆。玩家應保持理性，避免過度解讀短期現象。\n\n問題拋給你：面對資料的波動與偶發事件，應該如何調整心態與策略？",4,[18,27,34],{"slug":19,"type":20,"extremeSubtype":21,"publishAt":22,"coverImage":23,"viewCount":10,"title":24,"summary":25,"readMinutes":26},"2026-10-11-extreme-sum-zero-v2","extreme","E2","2026-10-11 11:56:58","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-sum-zero-v2.jpg","加拿大28第3492654期驚現和值0","加拿大28第3492654期開出總和值為0的極值，罕見機率僅0.1%。最近一次出現是在3492637期。",1,{"slug":28,"type":20,"extremeSubtype":29,"publishAt":30,"coverImage":31,"viewCount":10,"title":32,"summary":33,"readMinutes":26},"2026-10-11-extreme-triple-zero","E1","2026-10-11 11:56:49","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-triple-zero.jpg","加拿大28豹子號000再度出現，罕見機率僅1%","加拿大28第3492654期出現豹子號000，理論機率僅為1%。距離上次開出僅間隔約1小時。",{"slug":35,"type":20,"extremeSubtype":21,"publishAt":36,"coverImage":37,"viewCount":10,"title":38,"summary":39,"readMinutes":26},"2026-10-11-extreme-sum-zero","2026-10-11 10:46:56","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-sum-zero.jpg","加拿大28再現和值極端0事件","10月11日JND28第3492634期開獎出現極端和值0，理論機率僅0.1%，兩天內的第二次發生。",[41,46,52,58,63,69,75,81,87,93,99,105,111,117,123,129,135,141,146,152,158,164,170,176,182,188,194,200,206,212],{"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":57},"genetic_evolution","遗传进化算法","遺傳進化演算法","Genetic Evolution Algorithm",3,{"code":59,"nameZhCn":60,"nameZhTw":61,"nameEnUs":62,"sortOrder":16},"markov_chain","马尔可夫链","馬可夫鏈","Markov Chain",{"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]