The "Chain" tab in the AISHE system provides a comprehensive overview of results. It displays data from all AISHE client systems, up to a maximum of 30 systems, in weekly comparison. With this overview, users can quickly and easily compare the performance of different AI trading strategies and settings.
The comparison fields in the "Chain" tab include essential metrics such as total net profit, gross profit, gross loss, profit factor, expected payoff, absolute drawdown, maximal drawdown, maximal drawdown %, relative drawdown %, relative drawdown, total trades, short positions won, short positions won %, long positions won, long positions won %, profit trades total, profit trades (% of total), loss trades total, loss trades % of total, largest profit trade, largest loss trade, average profit trade, average loss trade, maximum consecutive wins, maximum consecutive wins ($), maximum consecutive losses, maximum consecutive losses ($), maximal consecutive profit $, maximal consecutive profit (count), maximal consecutive loss $, maximal consecutive loss (count), average consecutive wins, and average consecutive losses.
With this comprehensive overview of AI trading results, users can easily identify the strengths and weaknesses of their AISHE client system strategies and adjust their settings accordingly to achieve better profits.
7. Adjustment
The "Adjustment" tab allows users to customize their AISHE ID client system by making default or desired changes. This feature is referred to as the "interdependence chain and adjustment structure" and has two components: "Day setting" which applies only to the current day and is not a global setting, and a combination of "Adjust Daily Trading Requirements".
While it is recommended to leave everything unchanged, users with country-specific settings on their computers should check whether the table contains incorrect settings. If necessary, adjustments can be made here and entered into the configuration file or have them changed.
Please note that the settings in the "Adjustment" tab are quite complex and may require special treatment and explanation depending on the conditions. It is recommended to refer to the "Dash" tab for a comparison of settings to ensure optimal performance.
In addition to the previous description, it should also be mentioned that the language setting is a crucial aspect when making adjustments in the "Adjustment". It is important to ensure that the correct language is set for the specific AISHE client system to avoid possible problems or misunderstandings.
In addition, users have the option to freeze the currently visualized setting by selecting an AISHE client system and importing it using the "Don't read" checkbox. This feature allows users to carry those settings over to the next system to be selected, making the fitting process faster and more efficient.
8. Session
The "Session" tab in the AISHE client-system allows users to customize attribution settings for session times and values. With this level of customization, users can tailor the attribution settings to their specific needs, making it easier to track and analyze the performance of sessions.
Users can activate or deactivate mapping, session-based mapping, and reassignment in their customization settings, which enables the AISHE client-system to make data-driven decisions based on accurate performance tracking.
Customizing the AISHE client-system session settings can help achieve the goals more efficiently. With the "Session" tab, you have the ability to set attribution settings that are tailored to your unique needs, giving you a powerful tool.
9. State
The "State" tab in the AISHE system's Cloud State Control allows for easy template transfer between different AISHE clients. With the ability to selectively choose days and groups such as ETC, Indices, Forex, Crypt, and Shares, users can transfer the neural crypt values from one AISHE client to another. This can be particularly helpful for users who want to maintain consistency between their different AISHE clients or who want to transfer successful templates from one client to another. The process is simple and streamlined, making it easy for users to send neuronal state templates from one AISHE ID to another.
10. PL
The "PL" tab in AIman provides an experimental real-time forecast function that visualizes the direction of a symbol of your choice in real-time. This function allows users to see the short-term, medium-term, and long-term direction of a symbol within a time window of 5 minutes to 5 hours.
By utilizing advanced AI algorithms and neural networks, AIman is able to provide accurate forecasts of market trends and help users make informed trading decisions. The "PL" tab is a useful tool for traders who want to stay up-to-date on the latest market trends and make informed trading decisions based on real-time data.
11. VC
The "VC" tab refers to the value chain cloud files. In this section, existing templates are checked for their availability and displayed in a table format, divided into different session days and times. The suggested columns for the templates include Session1, Session2, Session3, Session4, Session5, Session6, MMB 4 Real, MMS 4 Real, Verkettung, Co. Lernen, Reports, Einstellung, State Timing, Autostart, and the date they were last modified.
During the initial installation, standard templates are provided with older timestamps that are automatically updated when any changes are made. Users can select customized templates from their AISHE group or have them automatically generated based on their preferences.
Users can also transfer the connections from one AISHE client to another. This can be especially useful for users who want to maintain consistency between their different AISHE clients or transfer successful templates from one client to another. The process is simple and streamlined, making it easy for users to send their connections from one AISHE ID to another.
12. Pntr
The "Pntr" tab in the Interdependence Chains Penetrator allows the user to copy and paste neural states from one area to another. This feature is useful for determining a competent architecture for the MMB/MMS by specifying the number and type of neural states and the number of M neurons in each layer.
Although the initial architecture may not be optimal, it can be iteratively optimized during training using auxiliary algorithms in the Aishe/Highway window. One family of these algorithms prunes state nodes based on the weight vector's small values after a certain number of training epochs, effectively eliminating unnecessary or redundant state nodes.
Each neural network consists of three types of layers: input, hidden, and output. The Pntr tab allows users to copy and paste these layers to create an efficient and optimized architecture for their AISHE client system. More information on these features is available in the Info PDF.
13. Col
The "CoL" tab (Collaboration) allows users to compare the results of neuronal states from multiple AISHE client systems that have been grouped together using Federated Learning. Federated Learning is a machine learning approach that enables multiple AISHE client systems to collaboratively train a shared neural network without exchanging their data with each other. This ensures that the privacy and security of the data are maintained, while still allowing the systems to learn from each other and improve their performance.
Using the "CoL" tab, users can analyze the results of their collaborative learning efforts based on Session 1 (24 hours). However, it is important to note that this feature is intended for the easy creation and setup of the AI system only, and should not be relied upon as a one-day solution. By analyzing the results of the collaborative learning process, users can identify areas where their system is performing well and areas where improvements can be made, allowing them to continuously refine and optimize their AI system.
14. Settings
The "Settings" tab provides an overview of the data exchange and monitoring settings configured in the "Drive" tab. Users can easily monitor the status of the cloud drive folders and the communication between AIman and the AISHE client systems. This tab does not require any additional configuration, as it simply displays the current settings and status of the system.
15. Drive
The "Drive" tab is where users can configure the cloud drive folders to facilitate data exchange between AIman and the AISHE client systems. By default, the GDrive drive is set to "g" and the work folder of AISHE clients is preset to "g:\shortcut-targets-by-id*_ai*". In addition, the AISHE client systems are automatically detected and displayed in this tab.
To ensure that AIman is able to access the necessary data for training, the demo account number of the MT4 used for training must be entered. If it has not been automatically recognized by AIman, the user should input it manually.
With the cloud drive folders set up correctly, AIman can easily access and exchange data with the AISHE client systems, enabling accurate and efficient training of the neural networks.
16. Symbols
The "Symbols" tab in AIman displays a comprehensive list of supported symbols from 155 countries in a table format. The table includes numerical information, country details, currency type, and ISO code for each symbol.
This feature provides a useful reference for users when owerview symbols for analysis and training, ensuring that they have access to a wide range of relevant and diverse data sources.