This section gives you quick and easy
detailed product information on Benchum Decision.
| User interface |
Windows application,
fully menu-driven, color-coded toolbars, online context-sensitive
help (What's This?), tooltips |
| Versions |
Single-user version
Network version
Web host version for intranets
|
| Update |
Download and upload via
FTP (File Transfer Protocol), password protection |
 |
|
System requirements
To use Benchum Decision effectively,
these are system requirements for all versions:
| Computer type |
IBM-compatible
Pentium PC |
| Operating system |
Microsoft Windows NT, 2000, XP, or Vista |
| Memory |
128 Mbytes of RAM |
| Hard disk |
300 Mbytes of available hard disk space |
| Video display |
VGA video 800x600 resolution
or higher, color mode of high color 16-bit or greater |
| Optional |
An Internet connection, plus an ISP (Internet
Service Provider) |
| Network
version |
Novell Netware or Microsoft
Windows network |
| Web host
version |
Windows NT, 2000, XP, Server or Vista,
Unix or Linux (on request) server |
|
|
Supported file formats
Benchum Decision can save the listed
report and image file formats, and open and save the listed spreadsheet
file formats. The internal database uses a proprietary component file
format.
| Reports |
PDF (Portable Document Format)
EPS (Encapsulated PostScript”) |
| Spreadsheets |
XML (Extensible Markup
Language)
TXT (Tabbed Text)
CSV (Comma Separated Values) |
| Images |
EMF (Enhanced Windows Metafile
Format)
BMP (Windows Bitmap)
TIFF (Tag Image File Format)
GIF (Graphic Interchange Format)
PNG (Portable Network Graphic)
JPEG (Joint Photographic Experts Group) |
|
|
Financial
and statistical functions All versions of Benchum Decision offer
the following functions in easy-to-understand groupings:
| Capital budgeting |
Net present
value, internal rate of return (IRR), modified IRR, payback,
profitability index, and others |
| Smoothing |
Moving average, exponential smoothing, polynomial
smoothing |
| Trend analysis |
Linear, exponential, multiplicative,
reciprocal, S-curve, quadratic, polynomial trend, test statistics |
| ARIMA |
Autoregressive integrated moving average
modeling;
rule based selection process, test statistics |
| Regression models |
Automatic variable selection:
forward (base model) and backward (maximum model) selection,
test statistics |
| Artificial neural networks |
Multilayered, feed forward networks with
back propagation learning |
| Expert
system |
Rule based, modular rule
bases for mini applications;
rule parser, inference interpreter with forward chaining, explanation
component |
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