object n. 1. 物,物體,物件。 2.目標(biāo) (of; for); 目的,宗旨。 3.【哲學(xué)】對象,客體,客觀 (opp. subject); 【語法】賓語。 4.〔口語〕(可笑或可憐的)人[物]。 a small [strange] object 小[奇怪]東西。 the object of study 研究的對象。 the direct [indirect] object 直接[間接]受詞。 What an object you have made (of) yourself! 〔口語〕你這家伙把自己搞得真不像樣子! attain [achieve, gain, secure] one's object 達(dá)到目的。 fail [succeed] in one's object 沒有達(dá)到[達(dá)到]目的。 for that object 為了那個(gè)目的。 no object 〔廣告用語〕怎樣都好,不成問題;沒有困難(Distance is no object. (待聘者)上班距離(遠(yuǎn)、近)不成問題)。 propose an objectto oneself = set an object before one 立志,立下目標(biāo)。 with that object in view 懷著那個(gè)目的。 vi. 1.反對,抗議,表示異議 (against, to)。 2.抱反感,不服氣,有意見。 vt. 提出…作反對的理由 (that)。 If you don't object. 假使你不反對。 I object. 〔英下院〕我反對。 I object against him that he is a hypocrite. 我反對他,因?yàn)樗莻€(gè)偽君子。 object to 1. 反對(I object to your doing that. 我反對你做那件事)。 2.討厭(I object very much to a wet weather. 我非常討厭潮濕的天氣)。 adj. -less 沒有目的[宗旨]的,沒有物像的。
object to 反對,不贊成; 反對;抗議,抱反感; 反對;抗議;不支持; 聲稱; 提出異議; 贊成……的人則認(rèn)為
Multi - object optimization of hybrid active power filter based on genetic algorithm 基于遺傳算法混合有源濾波器參數(shù)的多目標(biāo)優(yōu)化
Auto - - generating paper is a constrained multi - object optimization problem . this paper presents a way based on genetic algorithm ( ga ) to solve the problem . we define the crossover operator and mutation operator in the real coded and adjust the probabilities of crossover and mutation 系統(tǒng)實(shí)現(xiàn)采用三層組織結(jié)構(gòu),面向?qū)W習(xí)者、教師、管理員三類用戶,具有課程學(xué)習(xí)、作業(yè)、答疑、考試以及交流功能,同時(shí)采用java語言來構(gòu)建智能agent ,解決了個(gè)性化學(xué)習(xí)的問題。
Based on the analysis of the learning theory and instructionual design , we understand the procedure and regulation of learning , recognizing how to improve the learning environments and instructional procedure , so our its could implement on a better pedagogy theory ; presented in xml , the subject knowledge could be more suitable to be manipulated by computer tutor , to develop an individual learning environments . auto - generating paper is a constrained multi - object optimization problem , this paper presents a way based on genetic algorithm ( ga ) to solve the problem , and discuss how to choose an individual coding to improve the efficiency of ga according the problem ; when establishing the student model , we consider the mental factor as well as the cognitive factor 基于對學(xué)習(xí)理論和教學(xué)設(shè)計(jì)的分析、總結(jié),了解了人類學(xué)習(xí)活動(dòng)的過程和內(nèi)在規(guī)律,以及如何優(yōu)化學(xué)習(xí)環(huán)境和教學(xué)過程,從而使智能教學(xué)系統(tǒng)建立在先進(jìn)的教育理論基礎(chǔ)上;基于xml技術(shù)的學(xué)科知識(shí)表示,使它更便于計(jì)算機(jī)導(dǎo)師進(jìn)行加工,形成個(gè)性化的學(xué)習(xí)環(huán)境;自動(dòng)組卷是一個(gè)帶約束的多目標(biāo)優(yōu)化問題,本文提出通過遺傳算法來解決,并分析了如何根據(jù)實(shí)際問題選擇個(gè)性化的編碼方案,提高遺傳算法的效率;在建立學(xué)生模型時(shí),除了考廣西大學(xué)碩士論文基于web的智能教學(xué)系統(tǒng)的研究慮認(rèn)知因素還考慮了心理因素。
With the reference on the idea of management by objectives and trait of performance target , the determination of financial goal was analyzed by using the method of problem analysis , and the determination of managers " performance objects was also analyzed by using game theory with incomplete information . according to the methods of multi - objects optimization and the theory of invigoration , the principle of designing performance invigoration and the mechanism of mutual action of performance object and invigoration in provincial grid corporation were put forward 借鑒目標(biāo)管理的思想、考察效績目標(biāo)的特性,并運(yùn)用問題分析的方法,剖析了省級(jí)電網(wǎng)企業(yè)財(cái)務(wù)目標(biāo)確定的思路;運(yùn)用不完全信息靜態(tài)博弈理論分析了經(jīng)營者業(yè)績目標(biāo)確定的過程;依據(jù)多目標(biāo)優(yōu)化與激勵(lì)的方法,結(jié)合相關(guān)激勵(lì)理論的研究,提出了效績激勵(lì)機(jī)制設(shè)計(jì)的原則;概括提出了省級(jí)電網(wǎng)企業(yè)效績目標(biāo)與效績激勵(lì)的互動(dòng)機(jī)理。
Then a model was established for solving the problem of hybrid power unit matching by connecting optimization design with vehicle simulation , and the problem of power matching of hybrid power unit was solved with evolutionary algorithm according to single - object optimization and multi - object optimization separately 然后,將優(yōu)化設(shè)計(jì)與汽車仿真結(jié)合,建立了混合動(dòng)力系統(tǒng)優(yōu)化匹配問題的求解模型,并利用遺傳算法對混合動(dòng)力系統(tǒng)的功率匹配問題進(jìn)行了單目標(biāo)和多目標(biāo)優(yōu)化求解。
Depending on stratagem of continuable development , development programming of states or regions should go in for correspond development of nature , human being , society and economy , to be brief , correspond development of multi - object , so perfect means of resolving the settle of problems is to establish multi - object optimization models restricted by dynamic input - output equation 社會(huì)經(jīng)濟(jì)系統(tǒng)是一個(gè)復(fù)雜的動(dòng)態(tài)大系統(tǒng),在可持續(xù)發(fā)展戰(zhàn)略指導(dǎo)下,一個(gè)國家和地區(qū)的發(fā)展規(guī)劃應(yīng)追求的是自然、人、社會(huì)、經(jīng)濟(jì)的協(xié)調(diào)發(fā)展,即多個(gè)目標(biāo)的協(xié)調(diào)發(fā)展。因此,建立一個(gè)以動(dòng)態(tài)投入產(chǎn)出方程為核心約束的多目標(biāo)優(yōu)化模型成為解決此類問題的理想方法。
Based on national defense foundation scientific research project - reserch on technology of agile manufacture , the paper discusses running characteristic of the virtual enterprise , and summarizes the basic conception and theory of project management and the key technology which is used in designing the project management systems . the article offers hierarchy model and rule that describes the project in virtual enterprise . combining the characteristic of project management under the situation of virtual enterprise , the paper analyses project management systems architecture and adopts graphic means to found task flow model , realizes multi - object optimization of scheduled plan 本文結(jié)合國防基礎(chǔ)科研項(xiàng)目一敏捷化虛擬制造技術(shù)研究,分析了虛擬企業(yè)的運(yùn)行特點(diǎn),概述了項(xiàng)目管理及其支撐技術(shù)的概念和理論,結(jié)合虛擬企業(yè)環(huán)境下項(xiàng)目管理的特點(diǎn),給出了虛擬企業(yè)環(huán)境下項(xiàng)目的層次結(jié)構(gòu)模型及其描述規(guī)則,并分析了項(xiàng)目管理系統(tǒng)體系結(jié)構(gòu),采用圖形化方法建立了任務(wù)流模型,運(yùn)用最小時(shí)差和最小ls優(yōu)化法,實(shí)現(xiàn)了進(jìn)度計(jì)劃的多目標(biāo)優(yōu)化。
2 . a mathematic model of multi - object optimization about the stability allocation criteria of optical components has been set up . the linear sum - weight and probability theory are introduced to solve the mathematic model and to budget the stability of the function blocks and the optical components 2 、構(gòu)建了多目標(biāo)最優(yōu)化的光學(xué)元件穩(wěn)定性分析數(shù)學(xué)模型,以功能模塊及其所含光學(xué)元件為研究對象,采用線性加權(quán)和法和概率論理論,解決了功能模塊穩(wěn)定性指標(biāo)和光學(xué)元件穩(wěn)定性指標(biāo)分配問題。