Tsvagiridzo PaMitemo Yesarudzo Yemigodhi Yechikamu Chekugadzira Maitiro

Mundima yekuchera data, nzira dzinowanzo shandiswa dzekupatsanura dzinosanganisira tsigiro vector michina, neural network, Bayesian classification, etc. Iyo algorithms iri pamusoro apa inonyanya kunangana nekusarongeka kwedata kugovera, kuvimba nekutsigirwa kwedata hombe, uye kuchera hukama hwavo hwekushamwaridzana kuburikidza. zviyero zvakafanana. Inoshandiswa zvakanyanya muminda yakadai sekukanganisa kuongororwa. Nekudaro, muindasitiri yekugadzira michina, dhizaini yezvikamu zvezvikamu (senge saizi, kurongeka, nezvimwewo) zvave zvakaenzana, uye muhuinjiniya chaihwo, chikamu chega chega mudhatabhesi chinoenderana negwara rimwe chete rekuita. Nokudaro, kudzokorora kwehuwandu hwehuwandu hwemashoko hunenge hwakanyanya, uye huwandu hwemashoko huduku, husina kukodzera kune yakataurwa pamusoro apa algorithm processing. Naizvozvo, vaongorori vanowanzo shandisa rough set theory kutungamira kucherwa kwemitemo yekuita sarudzo.

Pamberi pemitemo yesarudzo yemigodhi, tinofanira kutanga tive nechokwadi chekuvimbika kwe data. Izvi zvinodaro nekuti muinjiniya chaimo, mamiriro ekushanda anogara achichinja munguva chaiyo. Kuti udzivise huwandu hudiki hweatypical data inogadzirwa neakakosha mamiriro ekushanda kubva pakukanganisa kuita sarudzo, data inoda kufanofanotaurwa. kubata. Naizvozvo, zvinyorwa zvinowanzo shandisa nzira yekuverenga rutsigiro uye chivimbo kuti uwane yakajairika process data.

Zvichienderana neiyo yakawedzera rough set modhi, iyo process yekuda ruzivo inocherwa nehukama hukama hwekuenzana, kufanana, uye zvido, izvo zvinosimbisa kuti maitiro ekuda ruzivo anogona kutungamira zvakananga kuita kwemugadziri, uye rough set theory haidi. the process rule feasibility evaluation link, iri nani pane vamwe. Nzira yekuchera iri nyore uye yakananga.

The rough set theory mining results zvinosanganisira deterministic mitemo yakawanikwa kubva yakaderera approximation set uye yakashata zone, uyewo asina chokwadi mitemo yemuganhu muganhu. Kuti ndinyatso chera migodhi yemitemo yenzvimbo yemuganhu, Zhang Z. et al. yakashandisa kushanduka kwakanyatsojeka rough set model kuti ipfuure kururamisa Zvichitevera kushanduka kwemaitiro emigodhi, huwandu hwepamusoro hwekuenzanisa seti hunoderedzwa zvinobudirira. Ruzivo rwemhando yepamusoro rwakamepurwa kuhukama hwehukama kuti vagadzire modhi yekusanganisa ruzivo, iyo inogona kunyatso kuchera mimwe mitemo yesarudzo.

Iyo yakakosha maitiro ehukasha seti kufunga ndeyekuwana iyo shoma hunhu kudzikiswa. Chen Hao et al. akaongorora kuderedza kusakanganiswa kunokonzerwa nepakati pekubatanidza uye nzvimbo yakanaka. Kune iyo yakasarudzika chaiyo yakakasharara seti modhi ine inogara yakarongeka chiyero uye inogara yakanaka domain, iyo yemukati-yakavakirwa Difference matrix uye hunhu musimboti kuti uwane hushoma hwekudzikisa hunhu. Uchishandisa heuristic reduction algorithm, tanga wawana iyo yakakosha hunhu, uye verenga kutsamira kwehunhu. Zvinoenderana nekukwira kurongeka kwekutsamira, hunhu uye kernel hunhu zvinosanganiswa mukutendeuka, uye pakupedzisira wowana Minimal hunhu kudzikiswa, funga.
Iyo inhomogeneity yekugovera sampuli inovandudzwa pahwaro hwenharaunda yakashata seti, uye K-yepedyo muvakidzani rough set modhi inokurudzirwa, iyo zvinobudirira kubvisa huwandu hukuru hwehunhu. Sarudzo yekutonga migodhi inonyanya kukamurwa kuita mhando mbiri, imwe ndeye inductive migodhi uye imwe yacho yekubvisa. Migodhi nzira. Pfungwa huru yekuchera migodhi ndeyekupfupikisa mitemo ine musoro yekuita sarudzo mune yakaoma data seti. Kana chinangwa chawanikwa, fananidza hunhu hwemutemo wakatarwa zvichienderana neanotarisirwa hunhu paramita, kuitira kuti ubvise mitemo yekuita sarudzo inoenderana nezvinodiwa. Pfungwa huru yekubvisa migodhi ndeyekupatsanura zvirimo musarudzo kuita musanganiswa wemaganho akati wandei, uye shandisa iyo data seti kuchera chiyero chekushandiswa kwemaseti esarudzo. Apo chinangwa chinowanikwa, maererano nechinangwa
Iyo inonangwa hunhu paramende inobvisa iyo yakakodzera-yekuita sarudzo subset, uye inoironga zvakare mune inodiwa kuita sarudzo yemukati. Kusiyana neizvi, mitemo yesarudzo yezvicherwa zvisinganzwisisiki zvakasiyana-siyana uye ine nzvimbo yakafara yekushandiswa, uye inductive mining ine zvipingamupinyi zvakasimba, izvo zvinogona kuvimbisa kuvimbika kwemitemo.

Mune magwaro ataurwa pamusoro apa, mazhinji ekugadzirisa nzira inductive mining. Kunyangwe kuvimbika kwemitemo yesarudzo kuchinyatso vimbiswa, iyo yakasimba inomanikidza zvakare inotungamira kune yakaderera kushandiswa kwedata uye inomisa kukwana kweiyo sarudzo yekutonga base. Uyezve, kunyangwe iyo shanduko yechokwadi yakakasharara seti inogona kudzikisa zvinobudirira nzvimbo yemuganhu, kukosha kwayo kunonyanya kuiswa neruzivo rwemanyorero, uye zvakawandisa zvinhu zvevanhu zvinoderedza kuvimbika kwekutonga kwesarudzo. Nokudaro, nzira yekuderedza nzvimbo yemuganhu uye kuvandudza kushanduka kwemitemo pamusana pekuona kuvimbika kwemitemo yekuita sarudzo ndiyo huru yekutsvaga hutungamiri hwemigodhi yekuita sarudzo yemitemo.

Batanidza kuchinyorwa ichi: Tsvagiridzo PaMitemo Yesarudzo Yemigodhi Yechikamu Chekugadzira Maitiro

Dzokorora Chirevo: Kana pasina mirairo yakakosha, zvinyorwa zvese zviri pasaiti ino ndezvepakutanga. Ndokumbira uratidze kwakabva kudhindazve: https://www.cncmachiningptj.com/, thanks!

PTJ CNC shopu inogadzira zvikamu zvine yakanakisa michina zvivakwa, kurongeka uye kudzokorora kubva kusimbi nepurasitiki. 5 akabatana CNC azvikuya iripo.Kugadzira yakakwira-tembiricha chiwanikwa range inclouding inconel machine,monel machine,Kugadziriswa kweGeek Ascology,Carp 49 machine,Hastelloy machine,Nitronic-60 machine,Hymu 80 kugadzira,Danho Simbi machine, nezvimwe.,. Yakanakira kunyorera nzvimbo.CNC machining inogadzira zvikamu zvine yakanakisa mehendi zvivakwa, kurongeka uye kudzokorora kubva pasimbi nepurasitiki. 3-axis & 5-axis CNC yekugaya iripo.Ticharonga pamwe newe kuti tipe yakanyanya-isingadhuri masevhisi ekukubatsira iwe kuti usvike kune chako chinangwa, Gamuchirai Kwatiri isu ( sales@pintejin.com ) zvakananga purojekiti yako nyowani.