[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reports-detail-2026-10-02-ai-performance-en-US":3,"reports-algorithms":41},{"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 Algorithm Performance: Highs and Lows in Accuracy","Canada 28 AI Algorithm Performance Revealed: Accuracy Highlights","On October 2, 2026, Canada 28 AI algorithms showcased mixed results. The standout 'Local Entropy' algorithm led with 46.63%, while 'Omission Reduction' trailed at 34.04%.","Yesterday's Canada 28 AI algorithm results showed a stark contrast, with 'Local Entropy' leading at 46.63% accuracy, while 'Omission Reduction' lagged at 34.04%.","## Highlights from Yesterday's AI Algorithm Performance\n\nYesterday's Canada 28 draws on October 2, 2026, featured 402 rounds, with AI algorithm performance taking center stage. The analysis focused on both the top and bottom performers, highlighting the standout 'Local Entropy' algorithm and the underwhelming performance of others.\n\n### Top Performers\n\nLeading the pack, the **Local Entropy algorithm achieved a remarkable overall accuracy of 46.63%**, with a prediction hit rate of 58.6%. Following closely were the Kelly Criterion and Random Forest algorithms, with overall accuracies of 46.63% and 46.33%, respectively. These three algorithms excelled not only in overall metrics but also across multiple subcategories.\n\nDeep Learning and Deep Neural Networks secured the fourth and fifth spots, with accuracies of 46.26% and 45.51%. This indicates that deep learning-based models continued to perform reliably in yesterday's data.\n\n### Bottom Performers\n\nOn the other end, the lowest-ranked algorithms included Omission Chasing, Omission Reduction, and Double-Step Transition. **The Omission Reduction algorithm had an overall accuracy of just 34.04%, roughly half that of the top algorithms**, suggesting these models struggled to capture critical statistical features in the current dataset.\n\n### Data Trends and Insights\n\nThe day's data distribution revealed interesting patterns. For example, span 5 appeared most frequently, with 62 occurrences. Combined with the average deviations in big\u002Fsmall and odd\u002Feven ratios (47.76% and 52.24%, respectively), these trends seemed to favor the prediction mechanisms of top-performing algorithms, while lower-performing models struggled with such skewed distributions.\n\n### Notable Events\n\nTwo rare triple number occurrences and an unusual total sum of 0 were recorded yesterday. While these events are statistically rare, they provide valuable scenarios for algorithm validation.\n\n### Conclusion\n\nThis analysis underscores the importance of selecting algorithms that align with the specific characteristics of the data. For players and researchers, adapting to the prevailing data trends is key to improving accuracy. We will continue monitoring these algorithms to uncover their strengths and potential breakthroughs in varying data conditions.",8,[18,27,35],{"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","Canada 28 Draw #3492654 Hits a Total Sum of 0","Canada 28 draw #3492654 recorded an extremely rare total sum of 0, with a probability of just 0.1%. The last similar result occurred in draw #3492637.",2,{"slug":28,"type":20,"extremeSubtype":29,"publishAt":30,"coverImage":31,"viewCount":10,"title":32,"summary":33,"readMinutes":34},"2026-10-11-extreme-triple-zero","E1","2026-10-11 11:56:49","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-triple-zero.jpg","Canada 28 Triple Number 000 Reappears, Rare 1% Probability","Canada 28's draw #3492654 featured the rare triple number 000, with a theoretical probability of just 1%. This marks the second occurrence within an hour.",3,{"slug":36,"type":20,"extremeSubtype":21,"publishAt":37,"coverImage":38,"viewCount":10,"title":39,"summary":40,"readMinutes":26},"2026-10-11-extreme-sum-zero","2026-10-11 10:46:56","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-sum-zero.jpg","Canada 28 Hits Rare Sum 0 Again","On October 11, JND28 draw #3492634 recorded an extremely rare sum of 0, with a theoretical probability of only 0.1%, marking the second occurrence in just two days.",[42,48,53,58,64,70,76,82,87,93,99,105,111,117,123,129,135,141,146,152,158,164,170,176,182,188,194,200,206,212],{"code":43,"nameZhCn":44,"nameZhTw":45,"nameEnUs":46,"sortOrder":47},"quantum_probability","量子概率引擎","量子機率引擎","Quantum Probability Engine",1,{"code":49,"nameZhCn":50,"nameZhTw":51,"nameEnUs":52,"sortOrder":26},"deep_neural_network","深度神经网络","深度神經網路","Deep Neural Network",{"code":54,"nameZhCn":55,"nameZhTw":56,"nameEnUs":57,"sortOrder":34},"genetic_evolution","遗传进化算法","遺傳進化演算法","Genetic Evolution Algorithm",{"code":59,"nameZhCn":60,"nameZhTw":61,"nameEnUs":62,"sortOrder":63},"markov_chain","马尔可夫链","馬可夫鏈","Markov Chain",4,{"code":65,"nameZhCn":66,"nameZhTw":67,"nameEnUs":68,"sortOrder":69},"deep_learning","深度学习","深度學習","Deep Learning",5,{"code":71,"nameZhCn":72,"nameZhTw":73,"nameEnUs":74,"sortOrder":75},"bayesian","贝叶斯推理","貝氏推論","Bayesian Inference",6,{"code":77,"nameZhCn":78,"nameZhTw":79,"nameEnUs":80,"sortOrder":81},"random_forest","随机森林","隨機森林","Random Forest",7,{"code":83,"nameZhCn":84,"nameZhTw":85,"nameEnUs":86,"sortOrder":16},"lstm","LSTM 长短期记忆","LSTM 長短期記憶","LSTM Network",{"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]