Z-Code System

Z-Code体育预测系统
Z-Code是一款经过长期公开测试验证的体育赛事预测系统,它结合了人类专家的智慧与强大的统计技术,能准确预测赛事结果并为用户带来稳定收益。
After Years Of Live Beta-testing On Facebook In Front Of Over 12,315Fans, Z-Code Finally Goes Private!
February 05, 2014: From The Desks of: Ron, Mike and Steve

Dear Facebook Follower And Valued Beta-Tester,

After years of development and months & months of live beta-testing on Facebook, we are finally ready. Z-Code System goes private!

We are closing Z-Code to the public, removing it from the sight of prying eyes (and the Las Vegas conglomerate of betting sharks that definitely do not want us to succeed) and we will use it only for the sake of our VIP members and obviously us, avid bettors and money makers.

Not much has to be said about this system, which is the pinnacle of our developer careers (even topping Fapturbo, I'd say)... because you, dear reader, shall experience it first-hand...

An Industry First...

Never has anyone in the betting niche given out a service or product to make money first and be charged later because they knew it would not work or that theirs would be a crappy product.

You know that Z-Code works because you followed us on facebook and/or saw people there make money... with STEADY GAINS!

... we wanted to prove to you upfront and LIVE that we've got something SPECIAL... something that can truly make a difference in your life, even if you are no sports fan or just a work-from-home mom who wants to make extra thousands a month.

You SAW us make money day in and day out, live and uncut, over facebook... more than 10,000 fans are proof of this.

In fact, Z-Code started to grow virally and more and more people came in by word of mouth... marvellous but dangerous as well, but let me explain.

In fact, over the beta-testing months, we generated huge amounts of cash for ourselves and much, much more for the beta-testing group.

The performance was fully verified by thousands of people who followed us on facebook during the last few months, commenting on every win or loss.

When you are winning, you don't have to hide your results. That’s why we agreed to perform a public monitoring of our results on an independent pick-monitor as well.

During the last 2 months, we followed our system and documented all picks so anyone could verify them. We even got into the top 5 world cappers with Z-Code!







What is Z-Code?

Z-Code could be called a "Betting Robot" but actually it is much, much more. Let me explain. 
Z-Code has been developed to provide us with winning sports predictions in:




Why these specific sports you ask?

Firstly, because they are popular and therefore allow high volume betting with the bookies (above 10s of thousands of $$$ per single bet) and second, because we wanted to rake in profits all year long and not just for a season or two while having to sit out all the other action.

Coming from the currency market scene (Forex), we decided that we wanted to have an "AUTOMATED" money-making system that would choose winning picks based on a precise and powerful prediction model.

We wanted to "trade" in the sports niche just like we traded currencies in the forex market. Little did we know that all the work would pay off in such a grand way!

Sports betting is a HUGE industry! Billions of dollars float out there waiting to be grabbed and with a mathematical approach, you can get the edge needed!!

Z-Code “ Trades” Sport!

It takes into account over 80 different parameters in every game such as player conditions, injuries, Home or Away team, goalies, past performance, predicted future performance, trainers, events, importance of match, rivalries, feuds, and so MUCH more, all to calculate a very precise outcome.

It’s Not Win Or Loss... It’s The “ Value

Z-Code is not looking for only a winner and a loser. It seeks the "value" in each game, where you can make the most money with the smallest risk possible... therefore it predicts bets such as "how many goals will fall" or " who's going to score the most points" or "will there be more than 5 goals or less"...

seeking the value in every game and giving you the most earnings!

Where Emotions Fail...  Calculations Prevail!

Z-Code is a robot!

... it`s a machine, a "code" so to speak... it has no favourite players or teams... it is ice cold and tracks performance & performance only! Handicappers that predict games tend to have favourites, even if they don`t admit it... their choices are emotional... and without 100% objectivity, you can never be as accurate as a proven prediction model... that`s why, we eat handicappers for breakfast!

After 27 months sitting in dark rooms studying algorithms and formulae, with an army of 21 programmers and paying salaries of well over $200,000 (!!) we finally hit the jackpot!

Z-CODE was born! And we started raking in profits while putting it to the test LIVE, making it available to thousands on our facebook beta-tester group!

It was very important to us because we wanted to PROVE, upfront without any shadow of a doubt, that Z-code would make each and every single user profits.

Z-Code pulls in profits on time, every time. We not only claim this, but prove it here... and NOW that Z-Code is consistently making big gains with:

  • 14 months of public beta-testing on Facebook.
  • The only system fully backtested back to 1999. Proven profitable, never having had a losing month... NOT ONCE!
  • Doubling accounts every month proven again by,
  • 2 Public verified accounts on a 3rd party monitor, one called Mike-Tester and the other one called The Xcode (that was renamed to Zcode)

Bankroll 1: 64 - 51, +$10,095 Profit. Account doubled. Click to verify
Bankroll 2: 109 - 105, +$10,163 Profit. Account doubled. Click to verify
Bankroll 3: 251 - 240, +$11,645 Profit. Account doubled. Click to verify
Bankroll 4: 293 - 71, +23,431.30 EUR Profit. Click to verify

We didn't just double those test accounts once... not just twice... but 3 times just for the sake of proving our claims!! After all, talk is cheap these days... you have to put your money where your mouth is!




But This Is Just The “TIP” Of The Iceberg...

Remember our 3 day journey where we posted picks of Z-Code in detail and showed people how to make money in 4 days from April 13th 2012 till April 17th ???

Download Those PDF Reports here and see for yourself how much money you would have made had you been a happy Z-Code camper!

4 Times LIVE Proof 100% Transparency 4 Days In A Row










Z-Code Technology

Imagine if you could have a sports betting system that can be truly profitable over the course of 11 years no matter if the team is winning or losing? Sounds great? I bet it does.

Today we are really excited to share our results with you and show how you can win with us!

We win because we combine the power of our human cappers who are experts in sports with the power of technology: statistical data since 1999. Our picks are documented and proven - each winning and losing pick is available for members to check and verify in the members zone.
We never hide any results.





Z-Code Prediction Model features:
80+ Parameters in calculation. Every single detail you can think of is there.
Automatic prediction model. Computer Generated picks
Hot Trends - easy to follow. Ride the winning trend.
Transparent Performance. Fully verified picks and predictions since 1999.
Backtest approach like in Forex. Each system goes through advance backtest and forward test.
We don't gamble. We TRADE SPORTS. When you want to grow your bankroll, there is no room for luck or chance. Only pure math and a statistical winning edge.







内容概要:本文提出了一种基于融合鱼鹰算法和柯西变异的改进麻雀优化算法(OCSSA),用于优化变分模态分解(VMD)的参数,进而结合卷积神经网络(CNN)与双向长短期记忆网络(BiLSTM)构建OCSSA-VMD-CNN-BILSTM模型,实现对轴承故障的高【轴承故障诊断】基于融合鱼鹰和柯西变异的麻雀优化算法OCSSA-VMD-CNN-BILSTM轴承诊断研究【西储大学数据】(Matlab代码实现)精度诊断。研究采用西储大学公开的轴承故障数据集进行实验验证,通过优化VMD的模态数和惩罚因子,有效提升了信号分解的准确性与稳定性,随后利用CNN提取故障特征,BiLSTM捕捉时间序列的深层依赖关系,最终实现故障类型的智能识别。该方法在提升故障诊断精度与鲁棒性方面表现出优越性能。; 适合人群:具备一定信号处理、机器学习基础,从事机械故障诊断、智能运维、工业大数据分析等相关领域的研究生、科研人员及工程技术人员。; 使用场景及目标:①解决传统VMD参数依赖人工经验选取的问题,实现参数自适应优化;②提升复杂工况下滚动轴承早期故障的识别准确率;③为智能制造与预测性维护提供可靠的技术支持。; 阅读建议:建议读者结合Matlab代码实现过程,深入理解OCSSA优化机制、VMD信号分解流程以及CNN-BiLSTM网络架构的设计逻辑,重点关注参数优化与故障分类的联动关系,并可通过更换数据集进一步验证模型泛化能力。
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