. . . "N\u00E1vrh modelu hodnocen\u00ED podnikov\u00E9 finan\u010Dn\u00ED situace" . . . . "Z(MSM6215648904)" . "N\u00E1vrh modelu hodnocen\u00ED podnikov\u00E9 finan\u010Dn\u00ED situace" . "Pokorn\u00FD, Martin" . . "3"^^ . . "Obsah p\u0159\u00EDsp\u011Bvku se zab\u00FDv\u00E1 mo\u017Enostmi automatizovan\u00E9ho vyhodnocov\u00E1n\u00ED finan\u010Dn\u00ED situace podniku a to za pomoci vyu\u017Eit\u00ED p\u0159\u00EDstup\u016F z oblasti um\u011Bl\u00E9 inteligence. Jak z klasick\u00FDch p\u0159\u00EDstup\u016F vypl\u00FDv\u00E1, kl\u00ED\u010Dov\u00E1 je prvotn\u00ED anal\u00FDza jednotliv\u00FDch finan\u010Dn\u00EDch ukazatel\u016F podniku. Vyhodnocov\u00E1n\u00ED finan\u010Dn\u00EDch ukazatel\u016F ve v\u00FDsledku vede k v\u00FDrazn\u00E9mu omezen\u00ED podnikatelsk\u00FDch rizik a umo\u017E\u0148uje v dlouhodob\u00E9m horizontu zajistit finan\u010Dn\u00ED stabilitu podniku. Obzvl\u00E1\u0161t\u011B Zejm\u00E9na u men\u0161\u00EDch podnik\u016F je to velmi pal\u010Div\u00FD probl\u00E9m, zejm\u00E9na pokud podnik nedisponuje fina\u010Dn\u00EDm expertem. Nebo\u0165 anal\u00FDza n\u011Bkdy velmi mnoha faktor\u016F, d\u00EDl\u010D\u00EDch finan\u010Dn\u00EDch ukazatel\u016F, je i pro odborn\u00EDka v dan\u00E9 oblasti n\u00E1ro\u010Dn\u00E1, je vhodn\u00E9 pou\u017E\u00EDt p\u0159\u00EDstupu tuto \u010Dinnost usnad\u0148uj\u00EDc\u00ED. Jako dobrou volbou se jev\u00ED nasazen\u00ED neuronov\u00E9 s\u00EDt\u011B na jej\u00EDm\u017E v\u00FDstupu je aproximovan\u00E9 \u0159e\u0161en\u00ED vypov\u00EDdaj\u00EDc\u00ED o finan\u010Dn\u00EDm stavu podniku. Takto lze \u0159e\u0161it jednozna\u010Dn\u00E9 p\u0159\u00EDpady av\u0161ak mnohdy \u010Dasov\u011B n\u00E1ro\u010Dn\u00E9 na vyhodnocen\u00ED expertem. P\u0159ed vlastn\u00ED klasifikac\u00ED je pot\u0159eba nau\u010Dit neuronovou s\u00ED\u0165 na vhodn\u00FDch datech. Pak je" . "N\u00E1vrh modelu hodnocen\u00ED podnikov\u00E9 finan\u010Dn\u00ED situace"@cs . "Trenz, Old\u0159ich" . . "N\u00E1vrh modelu hodnocen\u00ED podnikov\u00E9 finan\u010Dn\u00ED situace"@cs . . "978-80-7302-131-3" . . . "3"^^ . . "Obsah p\u0159\u00EDsp\u011Bvku se zab\u00FDv\u00E1 mo\u017Enostmi automatizovan\u00E9ho vyhodnocov\u00E1n\u00ED finan\u010Dn\u00ED situace podniku a to za pomoci vyu\u017Eit\u00ED p\u0159\u00EDstup\u016F z oblasti um\u011Bl\u00E9 inteligence. Jak z klasick\u00FDch p\u0159\u00EDstup\u016F vypl\u00FDv\u00E1, kl\u00ED\u010Dov\u00E1 je prvotn\u00ED anal\u00FDza jednotliv\u00FDch finan\u010Dn\u00EDch ukazatel\u016F podniku. Vyhodnocov\u00E1n\u00ED finan\u010Dn\u00EDch ukazatel\u016F ve v\u00FDsledku vede k v\u00FDrazn\u00E9mu omezen\u00ED podnikatelsk\u00FDch rizik a umo\u017E\u0148uje v dlouhodob\u00E9m horizontu zajistit finan\u010Dn\u00ED stabilitu podniku. Obzvl\u00E1\u0161t\u011B Zejm\u00E9na u men\u0161\u00EDch podnik\u016F je to velmi pal\u010Div\u00FD probl\u00E9m, zejm\u00E9na pokud podnik nedisponuje fina\u010Dn\u00EDm expertem. Nebo\u0165 anal\u00FDza n\u011Bkdy velmi mnoha faktor\u016F, d\u00EDl\u010D\u00EDch finan\u010Dn\u00EDch ukazatel\u016F, je i pro odborn\u00EDka v dan\u00E9 oblasti n\u00E1ro\u010Dn\u00E1, je vhodn\u00E9 pou\u017E\u00EDt p\u0159\u00EDstupu tuto \u010Dinnost usnad\u0148uj\u00EDc\u00ED. Jako dobrou volbou se jev\u00ED nasazen\u00ED neuronov\u00E9 s\u00EDt\u011B na jej\u00EDm\u017E v\u00FDstupu je aproximovan\u00E9 \u0159e\u0161en\u00ED vypov\u00EDdaj\u00EDc\u00ED o finan\u010Dn\u00EDm stavu podniku. Takto lze \u0159e\u0161it jednozna\u010Dn\u00E9 p\u0159\u00EDpady av\u0161ak mnohdy \u010Dasov\u011B n\u00E1ro\u010Dn\u00E9 na vyhodnocen\u00ED expertem. P\u0159ed vlastn\u00ED klasifikac\u00ED je pot\u0159eba nau\u010Dit neuronovou s\u00ED\u0165 na vhodn\u00FDch datech. Pak je"@cs . "[7FA76EC8C856]" . . "Luha\u010Dovice" . . "RIV/62156489:43110/07:00113817!RIV08-MSM-43110___" . "2"^^ . . "76;77" . . . "financial situation; company; klassification; decision making; expert; neuronal network"@en . "Obchod a spot\u0159ebitel '07" . . . "Konvoj" . "436404" . "Draft of Financial Situation Assessment Model Using"@en . "Brno" . "43110" . "Content of the article deals with possibilities of computerized evaluation of company financial situation by using artificial intelligence procedures. Classical conception implies that most important factor is the primary analysis of company financial indicators. The evaluation of financial indicator leads to strong limitation of enterprise risk and makes possible to ensure company financial stability. Especially for smaller companies it is a very serious problem, particularly if the company doesn't have financial expert. Someting the analysis can consist of many factors that even experts have problems to solve. In this case it is proper to use some concepts to make this activity easier. The neural network seems to be a good choice predicative situation evaluation, the neural network output approximated financial status of company. By using this way it's possible to solve clear cases which are time-consuming for expert. Before the true classification it's necessary to teach the neural network on pr"@en . "2007-09-05+02:00"^^ . . "Redlichov\u00E1, Radka" . "Draft of Financial Situation Assessment Model Using"@en . "RIV/62156489:43110/07:00113817" .