Add Chinese article digests and English-linked translation placeholders

articles/2024-10-13-neural-network-classification.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2024-10-13-neural-network-classification/
 alternate_en: /articles/2024-10-13-neural-network-classification/
 alternate_ru: /ru/articles/2024-10-13-neural-network-classification/
+alternate_zh: "/zh-cn/articles/2024-10-13-neural-network-classification/"
 preview_image: /static/images/articles/2024-10-13-neural-network-classification/01-classification.webp
 preview_text: 'One of my earliest articles on neural networks, based on teaching materials from 2008. We examine the perceptron, supervised learning, linear class separation, and the AND, OR and XOR functions: the basic mathematics behind neural networks.'
 cover_image: /static/images/articles/2024-10-13-neural-network-classification/02-perceptron.png

articles/2024-12-01-modified-hampel-filter.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2024-12-01-modified-hampel-filter/
 alternate_en: /articles/2024-12-01-modified-hampel-filter/
 alternate_ru: /ru/articles/2024-12-01-modified-hampel-filter/
+alternate_zh: "/zh-cn/articles/2024-12-01-modified-hampel-filter/"
 preview_image: /static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png
 preview_text: 'What makes a value anomalous, and how do we detect it? We examine a modified Hampel filter: the robustness of the median, MAD, sliding windows and threshold selection. With formal definitions, Python examples and an experiment using synthetic market data.'
 cover_image: /static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png

articles/2025-04-10-fuzzy-scales.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2025-04-10-fuzzy-scales/
 alternate_en: /articles/2025-04-10-fuzzy-scales/
 alternate_ru: /ru/articles/2025-04-10-fuzzy-scales/
+alternate_zh: "/zh-cn/articles/2025-04-10-fuzzy-scales/"
 preview_image: /static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png
 preview_text: How do you assess a system that is mostly secure, with a moderate level of risk? We explain fuzzy measurement scales, membership functions and transitions between levels, using examples from cybersecurity, data analysis and trading-signal assessment.
 cover_image: /static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png

articles/2025-04-16-hampel-anomalies-filtering.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2025-04-16-hampel-anomalies-filtering/
 alternate_en: /articles/2025-04-16-hampel-anomalies-filtering/
 alternate_ru: /ru/articles/2025-04-16-hampel-anomalies-filtering/
+alternate_zh: "/zh-cn/articles/2025-04-16-hampel-anomalies-filtering/"
 preview_image: /static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png
 preview_text: Measurement errors, network failures and price spikes are common. We show how to find these anomalies quickly using the median, MAD and a sliding window, from the basic idea of the Hampel filter to its applications in data analysis and algorithmic trading.
 cover_image: /static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png

articles/2025-04-22-target-probability.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2025-04-22-target-probability/
 alternate_en: /articles/2025-04-22-target-probability/
 alternate_ru: /ru/articles/2025-04-22-target-probability/
+alternate_zh: "/zh-cn/articles/2025-04-22-target-probability/"
 preview_image: /static/images/articles/2025-04-22-target-probability/Girls-and-probability.png
 preview_text: Real markets contain noise, outliers and uncertainty. We explain how to use historical data to estimate the probability of reaching a target, why prices need cleaning before calculation, and how to express the result as an understandable fuzzy assessment. With examples and diagrams.
 cover_image: /static/images/articles/2025-04-22-target-probability/Girls-and-probability.png

articles/2025-04-28-trading-algorithm.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2025-04-28-trading-algorithm/
 alternate_en: /articles/2025-04-28-trading-algorithm/
 alternate_ru: /ru/articles/2025-04-28-trading-algorithm/
+alternate_zh: "/zh-cn/articles/2025-04-28-trading-algorithm/"
 preview_image: /static/images/articles/2025-04-28-trading-algorithm/Girls-and-signals.png
 preview_text: 'How do market data become a trading signal? We follow the whole process: outlier filtering, target-attainability estimates, fuzzy signal strength, rules for opening and closing positions, and capital management. The architecture of our algorithm as it stood in 2025.'
 cover_image: /static/images/articles/2025-04-28-trading-algorithm/Girls-and-signals.png

articles/2025-05-13-trading-algorithm-history.md

@@ -12,6 +12,7 @@ series_url: /FMA/
 permalink: /articles/2025-05-13-trading-algorithm-history/
 alternate_en: /articles/2025-05-13-trading-algorithm-history/
 alternate_ru: /ru/articles/2025-05-13-trading-algorithm-history/
+alternate_zh: "/zh-cn/articles/2025-05-13-trading-algorithm-history/"
 preview_image: /static/images/articles/2025-05-13-trading-algorithm-history/promo-3.png
 preview_text: 'From the first Python scripts and sketches on paper to a signal algorithm: how, since 2015, we studied trends, formalised risk and target attainability, created PriceGenerator and built a decision-making system. Complete with drafts, charts and mistakes.'
 cover_image: /static/images/articles/2025-05-13-trading-algorithm-history/promo-3.png

ru/articles/2024-10-13-neural-network-classification.md

@@ -13,6 +13,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2024-10-13-neural-network-classification/
 alternate_en: /articles/2024-10-13-neural-network-classification/
 alternate_ru: /ru/articles/2024-10-13-neural-network-classification/
+alternate_zh: "/zh-cn/articles/2024-10-13-neural-network-classification/"
 preview_image: /static/images/articles/2024-10-13-neural-network-classification/01-classification.webp
 preview_text: Одна из моих первых статей о нейросетях — по учебным материалам 2008 года. Разбираем устройство персептрона, обучение с учителем, линейное разделение классов и функции AND, OR и XOR. Та самая базовая математика, с которой удобно начинать знакомство с нейросетями.
 cover_image: /static/images/articles/2024-10-13-neural-network-classification/02-perceptron.png

ru/articles/2024-12-01-modified-hampel-filter.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2024-12-01-modified-hampel-filter/
 alternate_en: /articles/2024-12-01-modified-hampel-filter/
 alternate_ru: /ru/articles/2024-12-01-modified-hampel-filter/
+alternate_zh: "/zh-cn/articles/2024-12-01-modified-hampel-filter/"
 preview_image: /static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png
 preview_text: 'Что считать аномалией в числовом ряду и как её найти? Разбираем модифицированный метод Хампеля: устойчивость медианы, MAD, скользящие окна и настройку порога. С формальными определениями, примерами на Python и экспериментом на сгенерированных биржевых данных.'
 cover_image: /static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png

ru/articles/2025-04-10-fuzzy-scales.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2025-04-10-fuzzy-scales/
 alternate_en: /articles/2025-04-10-fuzzy-scales/
 alternate_ru: /ru/articles/2025-04-10-fuzzy-scales/
+alternate_zh: "/zh-cn/articles/2025-04-10-fuzzy-scales/"
 preview_image: /static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png
 preview_text: Как оценить систему, если она «скорее безопасна», а риск — «умеренный»? Объясняем, как устроены нечёткие измерительные шкалы, функции принадлежности и переходы между уровнями. На примерах кибербезопасности, анализа данных и оценки торговых сигналов.
 cover_image: /static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png

ru/articles/2025-04-16-hampel-anomalies-filtering.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2025-04-16-hampel-anomalies-filtering/
 alternate_en: /articles/2025-04-16-hampel-anomalies-filtering/
 alternate_ru: /ru/articles/2025-04-16-hampel-anomalies-filtering/
+alternate_zh: "/zh-cn/articles/2025-04-16-hampel-anomalies-filtering/"
 preview_image: /static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png
 preview_text: 'Ошибки измерений, сетевые сбои и ценовые всплески встречаются постоянно. Показываем, как быстро находить такие аномалии с помощью медианы, MAD и скользящего окна: от простой идеи фильтра Хампеля до примеров его применения в анализе данных и алгоритмическом трейдинге.'
 cover_image: /static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png

ru/articles/2025-04-22-target-probability.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2025-04-22-target-probability/
 alternate_en: /articles/2025-04-22-target-probability/
 alternate_ru: /ru/articles/2025-04-22-target-probability/
+alternate_zh: "/zh-cn/articles/2025-04-22-target-probability/"
 preview_image: /static/images/articles/2025-04-22-target-probability/Girls-and-probability.png
 preview_text: На реальном рынке есть шум, выбросы и неопределённость. Рассказываем, как по историческим данным оценивать вероятность достижения целевого уровня, зачем очищать цены перед расчётом и как переводить результат в понятную нечёткую оценку. С примерами и схемами.
 cover_image: /static/images/articles/2025-04-22-target-probability/Girls-and-probability.png

ru/articles/2025-04-28-trading-algorithm.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2025-04-28-trading-algorithm/
 alternate_en: /articles/2025-04-28-trading-algorithm/
 alternate_ru: /ru/articles/2025-04-28-trading-algorithm/
+alternate_zh: "/zh-cn/articles/2025-04-28-trading-algorithm/"
 preview_image: /static/images/articles/2025-04-28-trading-algorithm/Girls-and-signals.png
 preview_text: 'Как из рыночных данных получается торговый сигнал? Разбираем всю цепочку: фильтрацию выбросов, оценку достижимости цели, нечёткую силу сигнала, правила открытия и закрытия позиций и управление капиталом. Историческая архитектура нашего алгоритма образца 2025 года.'
 cover_image: /static/images/articles/2025-04-28-trading-algorithm/Girls-and-signals.png

ru/articles/2025-05-13-trading-algorithm-history.md

@@ -12,6 +12,7 @@ series_url: /ru/FMA/
 permalink: /ru/articles/2025-05-13-trading-algorithm-history/
 alternate_en: /articles/2025-05-13-trading-algorithm-history/
 alternate_ru: /ru/articles/2025-05-13-trading-algorithm-history/
+alternate_zh: "/zh-cn/articles/2025-05-13-trading-algorithm-history/"
 preview_image: /static/images/articles/2025-05-13-trading-algorithm-history/promo-3.png
 preview_text: 'От первых Python-скриптов и набросков на бумаге до сигнального алгоритма: рассказываем, как с 2015 года исследовали тренды, формализовали риск и достижимость целей, создавали PriceGenerator и собирали систему принятия решений. С черновиками, графиками и ошибками.'
 cover_image: /static/images/articles/2025-05-13-trading-algorithm-history/promo-3.png

zh-cn/articles/2024-10-13-neural-network-classification.md

@@ -0,0 +1,25 @@
+---
+layout: "article"
+lang: "zh-CN"
+title: "神经网络中的线性与非线性分类"
+description: "从感知机、监督学习到 AND、OR、XOR，理解神经网络实现线性与非线性分类的基础数学。简体中文全文译文准备中。"
+keywords: "神经网络, 感知机, 监督学习, 线性分类, 非线性分类, XOR, FMA Research"
+date: "2024-10-13"
+author: "Timur Gilmullin"
+series: "FMA Research"
+series_url: "/zh-cn/FMA/"
+permalink: "/zh-cn/articles/2024-10-13-neural-network-classification/"
+alternate_en: "/articles/2024-10-13-neural-network-classification/"
+alternate_ru: "/ru/articles/2024-10-13-neural-network-classification/"
+alternate_zh: "/zh-cn/articles/2024-10-13-neural-network-classification/"
+preview_image: "/static/images/articles/2024-10-13-neural-network-classification/01-classification.webp"
+preview_text: "这篇神经网络入门文章源自作者 2008 年的教学材料。从感知机和监督学习出发，介绍线性分类，并通过 AND、OR、XOR 逻辑函数说明神经网络背后的基础数学。"
+cover_image: "/static/images/articles/2024-10-13-neural-network-classification/02-perceptron.png"
+translation_status: "placeholder"
+---
+
+> 简体中文全文译文正在准备中。您可以先阅读[英文原文](/articles/2024-10-13-neural-network-classification/)。
+
+## 内容摘要
+
+{{ page.preview_text }}

zh-cn/articles/2024-12-01-modified-hampel-filter.md

@@ -0,0 +1,25 @@
+---
+layout: "article"
+lang: "zh-CN"
+title: "利用改进型 Hampel 滤波器快速检测数值序列中的异常"
+description: "通过中位数、MAD、滑动窗口和阈值，理解改进型 Hampel 滤波器的异常检测方法与实验。简体中文全文译文准备中。"
+keywords: "异常检测, Hampel 滤波器, 中位数, 中位数绝对偏差, MAD, 滑动窗口, Python, FMA Research"
+date: "2024-12-01"
+author: "Timur & Mansur Gilmullin"
+series: "FMA Research"
+series_url: "/zh-cn/FMA/"
+permalink: "/zh-cn/articles/2024-12-01-modified-hampel-filter/"
+alternate_en: "/articles/2024-12-01-modified-hampel-filter/"
+alternate_ru: "/ru/articles/2024-12-01-modified-hampel-filter/"
+alternate_zh: "/zh-cn/articles/2024-12-01-modified-hampel-filter/"
+preview_image: "/static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png"
+preview_text: "什么样的数值才算异常，又该如何识别？本文介绍改进型 Hampel 滤波器如何利用中位数的稳健性、中位数绝对偏差（MAD）、滑动窗口与阈值检测异常，并给出形式化定义、Python 示例和基于合成市场数据的实验。"
+cover_image: "/static/images/articles/2024-12-01-modified-hampel-filter/digest-robot-1200x630.png"
+translation_status: "placeholder"
+---
+
+> 简体中文全文译文正在准备中。您可以先阅读[英文原文](/articles/2024-12-01-modified-hampel-filter/)。
+
+## 内容摘要
+
+{{ page.preview_text }}

zh-cn/articles/2025-04-10-fuzzy-scales.md

@@ -0,0 +1,25 @@
+---
+layout: "article"
+lang: "zh-CN"
+title: "当“是”与“否”还不够：模糊评价尺度的工作原理"
+description: "通过网络安全、数据分析和交易信号示例，理解模糊评价尺度、隶属函数与等级之间的过渡。简体中文全文译文准备中。"
+keywords: "模糊逻辑, 模糊评价尺度, 隶属函数, 网络安全, 数据分析, 交易信号, FMA Research"
+date: "2025-04-10"
+author: "Timur & Mansur Gilmullin"
+series: "FMA Research"
+series_url: "/zh-cn/FMA/"
+permalink: "/zh-cn/articles/2025-04-10-fuzzy-scales/"
+alternate_en: "/articles/2025-04-10-fuzzy-scales/"
+alternate_ru: "/ru/articles/2025-04-10-fuzzy-scales/"
+alternate_zh: "/zh-cn/articles/2025-04-10-fuzzy-scales/"
+preview_image: "/static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png"
+preview_text: "一个系统“总体安全”，但仍存在“中等风险”，该如何评价？本文介绍模糊评价尺度、隶属函数及不同等级之间的过渡，并结合网络安全、数据分析和交易信号评估说明其用法。"
+cover_image: "/static/images/articles/2025-04-10-fuzzy-scales/Girls-and-scales.png"
+translation_status: "placeholder"
+---
+
+> 简体中文全文译文正在准备中。您可以先阅读[英文原文](/articles/2025-04-10-fuzzy-scales/)。
+
+## 内容摘要
+
+{{ page.preview_text }}

zh-cn/articles/2025-04-16-hampel-anomalies-filtering.md

@@ -0,0 +1,25 @@
+---
+layout: "article"
+lang: "zh-CN"
+title: "无需复杂模型的快速异常检测：Hampel 方法"
+description: "从中位数、MAD 和滑动窗口出发，了解 Hampel 方法如何检测数据异常及其实际应用。简体中文全文译文准备中。"
+keywords: "异常检测, Hampel 方法, 中位数, MAD, 滑动窗口, 数据分析, 算法交易, FMA Research"
+date: "2025-04-16"
+author: "Timur & Mansur Gilmullin"
+series: "FMA Research"
+series_url: "/zh-cn/FMA/"
+permalink: "/zh-cn/articles/2025-04-16-hampel-anomalies-filtering/"
+alternate_en: "/articles/2025-04-16-hampel-anomalies-filtering/"
+alternate_ru: "/ru/articles/2025-04-16-hampel-anomalies-filtering/"
+alternate_zh: "/zh-cn/articles/2025-04-16-hampel-anomalies-filtering/"
+preview_image: "/static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png"
+preview_text: "测量误差、网络故障和价格尖峰都可能在数据中形成异常。本文从中位数、中位数绝对偏差（MAD）与滑动窗口出发，解释 Hampel 滤波器的基本思路，并介绍它在数据分析和算法交易中的应用。"
+cover_image: "/static/images/articles/2025-04-16-hampel-anomalies-filtering/Girls-and-Hampel.png"
+translation_status: "placeholder"
+---
+
+> 简体中文全文译文正在准备中。您可以先阅读[英文原文](/articles/2025-04-16-hampel-anomalies-filtering/)。
+
+## 内容摘要
+
+{{ page.preview_text }}

zh-cn/articles/2025-04-22-target-probability.md

@@ -0,0 +1,25 @@
+---
+layout: "article"
+lang: "zh-CN"
+title: "价格能否触及目标？用概率估计代替猜测"
+description: "利用历史数据估计目标价位的触及概率，并说明数据清洗与模糊评价在这一过程中的作用。简体中文全文译文准备中。"
+keywords: "目标价位, 触及概率, 概率估计, 数据清洗, 模糊评价, 算法交易, FMA Research"
+date: "2025-04-22"
+author: "Timur & Mansur Gilmullin"
+series: "FMA Research"
+series_url: "/zh-cn/FMA/"
+permalink: "/zh-cn/articles/2025-04-22-target-probability/"
+alternate_en: "/articles/2025-04-22-target-probability/"
+alternate_ru: "/ru/articles/2025-04-22-target-probability/"
+alternate_zh: "/zh-cn/articles/2025-04-22-target-probability/"
+preview_image: "/static/images/articles/2025-04-22-target-probability/Girls-and-probability.png"
+preview_text: "真实市场充满噪声、异常值和不确定性。本文介绍如何根据历史数据估计价格触及目标的概率，为什么计算前需要清洗价格数据，以及如何将结果转化为易于理解的模糊评价，并结合示例与图解说明。"
+cover_image: "/static/images/articles/2025-04-22-target-probability/Girls-and-probability.png"
+translation_status: "placeholder"
+---
+
+> 简体中文全文译文正在准备中。您可以先阅读[英文原文](/articles/2025-04-22-target-probability/)。
+
+## 内容摘要
+
+{{ page.preview_text }}