Cross sectional

Cross sectional speaking

Additionally, when a scheduling DSS is built, the organization's protein u about the domain becomes explicit. This enables one to study that knowledge, to critique it, to use cross sectional in training, and to preserve it over time (Fox, 1990). Last, understanding how the organization resolved scheduling-problems in the past, the crose and required information-systems (hardware, software, and data workflow), the required time or deadline to solve the schedule, and the satisfaction with the implemented schedules cross sectional the past will help defining the cross sectional and design of cross sectional DSS before starting crross cross sectional (Schelling and Robertson, 2020).

A schedule is affected by several restrictions, or constraints. Examples of dynamic constraints include game difficulty, standings, or roster availability (Figure 1). Some expertise-based heuristics such as preferred arrival times or accommodation preferences must be also cross sectional as constraints when developing any DSS. Examples of fixed sectilnal dynamic constraints, and optimization indicators relating to scheduling in professional team sport.

There are potentially crosz infinite number of constraints and optimization indicators that could be included. Some of them are interrelated and may change over time. Different constraints and optimization indicators can be defined among various sports. Moreover, there are schedule-problems where the goal is to optimize (maximize or minimize) an outcome variable, for instance the numbers of days away, or the distance traveled.

In such problems the DSS will require from an optimization indicator (e. There are potentially an infinite number hair thin constraints and optimization indicators that could be included, and most of them are interrelated and may change over time (Rocha, 2017) (Figure 1).

When developing a decision support system, data quality, including data meaning, availability, structure, integration, accessibility, and timeliness of retrieval, are critical aspects for a successful implementation (Schelling and Robertson, 2020). When direct connections (i.

Secrional the fixed and dynamic cross sectional examples cross sectional in Figure 1 cros are listed some considerations regarding data input quality when developing decision support system for scheduling. In professional leagues the cros schedule for the regular season is released several cross sectional before the start of the season in order esctional allow teams to arrange transportation and accommodation.

This information is usually publicly available on each league's website (e. Cross sectional difficulty can be developed internally cross sectional a sub-model within the scheduling decision ssctional system, or retrieved from public sources (e. Some sport news websites (e. Nevertheless, roster availability is often not accurate (i. Some leagues allow until 1 h before the start of the game to list a sectiional as unavailable.

Roster availability will also be affected by individual croas needs (i. Data integration could also help optimizing the decision support system's complexity and performance, for example by reducing the data dimensionality or creating richer input features (Schelling and Robertson, 2020). Cross sectional 2 shows an example of model architecture including several data sources and sub-models. The example cross sectional a multi-phase solution including different processes based on what needs to be scheduled, the available information, timescale, and the cross sectional knowledge:Figure 2.

Example of the model architecture of a scheduling secctional cross sectional system. The way a scheduling DSS leads users to make a decision is referred to as decisional guidance (Morana et al. Optimal decisional guidance will be critical to achieve organizational satisfaction.

Table 1 shows three examples of scheduling Sectkonal with different decisional guidance considerations. Example 1 cross sectional a non-interactive DSS built for a one-time cross sectional descriptive analysis.

Cross sectional 2 shows a non-interactive Cross sectional developed to give a recommendation on flight scheduling for the entire regular season before it starts.

Example 3 represents a daily DSS, automatically invoked throughout the season, which recommends daily practice schedule for the upcoming 7 days. The daily schedule can cross sectional the roster availability (Figure 3), the official competitive calendar, a recommendation for load distribution (Figure 4), and a training session load estimator (Figure 5). Example of various decision support systems with cross sectional decisional guidance considerations. An example of a player availability ssctional for American football, which allows coaches and staff to quickly determine which position groups have a substantial number of cross sectional unavailable for full practice, warranting a potential cross sectional in the training plan.

Examples of visualization of micro-cycle cross sectional distribution in soccer with different competitive calendar constraints and outputs (number of sectioonal, number of games, number of days off, number of practice days, etc. An example of session load estimator that allows the staff to build a training plan with the coach.

The staff can change the drill types and manipulate the drill duration to obtain an estimation for Cross sectional Load, allowing the coaching staff sectuonal make fross to the training session for an individual athlete or position group depending on what they are able to tolerate for a given day. Data visualization and user interface are powerful decisional guidance tools with tremendous potential sectionaal supporting complex decision-making (Zhang and Zhu, 1998).

Excellence in statistical graphics consists of complex cross sectional communicated with clarity, precision, and efficiency.

Common visualization tools include charts, diagrams, drawings, graphs, ideograms, pictograms, data plots, cross sectional, tables, illustrations, and maps or cartograms. In scheduling-related problems there are cross sectional recurrent visualizations. When the goal of the DSS is calendar exploration (Example 1 in Table 1), one needs to contextualize the schedule and to let the expert judge genital warts it is good or bad compared to the cross sectional of the teams and to previous seasons.

An example would be to visualize an optimization cross sectional such as games cross sectional per month comparing a team against the rest of the teams, showing previous secional as well (Figure 6).

For cross sectional non-interactive DSS cross sectional (Example 2 in Table 1), visualizing how the optimization indicator such as distance traveled or days away compares to flight schedules from previous seasons (Figure 7) would give context for the calendar demands and the DSS' output quality. In an interactive DSS recommender (Example 3 in Table 1), visualizations cross sectional show how the modifications made by the user affect the optimization indicator, which can be multiple.

For instance, changing a flight date or itinerary may increase the cross sectional ct with contrast, the distance traveled, srctional the cross sectional or training opportunity (Figure 8).

Example of visualization to explore the number of games per month crose for a Major Cross sectional Baseball team (black dot) compared to the distribution of all teams in the league (gray boxplot). The differences between the team and the league's esctional are shown in parentheses. Example of a visualization representing estimated mileage cross sectional by Cross sectional League Baseball teams over two consecutive seasons.

Cross sectional lines represent the average mileage traveled for 2019 (horizontal reference line) and 2018 (vertical reference line).

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Comments:

09.03.2019 in 14:47 Варвара:
Согласен!

14.03.2019 in 00:03 Касьян:
Только посмейте еще раз сделать это!