The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 28-187
Full Name: Valeriu Lupu
Position: Associate Professor
Age: ON
Sex: Male
Address: Mihai Viteazu Nr. 5 Bl. 5 Sc. B Ap. 20 Suceava, 720057
Country: ROMANIA
Tel: +40722627195
Tel prefix:
Fax: +40330814375
E-mail address: valeriul@seap.usv.ro
Other E-mails: catalinlupu@seap.usv.ro
Title of the Paper: The implementation of clean production and the use of neural networks in forecasting waste management
Authors as they appear in the Paper: Valeriu Lupu, Catalin Lupu, Nicolae Morariu
Email addresses of all the authors: valeriul@seap.usv.ro, catalinlupu@seap.usv.ro, nmorariu@eed.usv.ro
Number of paper pages: 15
Abstract: : In this article we present: ľ the implementation of "clean production" which means production based on careful evaluation of the product since its design phase to ensure that both the product and processes related to it at all stages of its life cycle (ranging the extraction of raw materials, manufacturing, packaging, consumer / use, waste collection and treatment) promotes the interests of the community, in particular as regards the environment. Clean production has four main elements: - Caution, which involves taking measures insurers even in the case of yet unconfirmed suspicions concerning a potential nocivitate to human health or the environment; - Prevention, as expression of conscience that is cheaper and more efficient to prevent environmental degradation than to provide remedies; - Democratic participation in decision-making of all stakeholders - An integrated and holistic approach. ľ a new concept taking in consideration the sweepings administra!
tion and which consist in: 1. the employment of neuronal network for predict serial time representing sweepings amount which are collected from population in time. The problems of prediction the serial time can be associated with neuronal network call ¡§feed-forward¡¨. Number of entrances unities are equal than number of emergences unities. The number of emergences unities represents the target of prediction. The prediction ¡§one step before¡¨ can be realized with an emergences unities network, and the prediction with ¡§K steps before¡¨ can be associate to a network with K emergences unities. Examples: 1. A model of a neuronal network ¡§one step before¡¨, which use six terms of serial time to predict the next term of series ( 6 neurons at entrance, 15 in hide tier and one in emergence tier, entering ==(xt-1, xt-2, xt-3, xt-4, xt-5, xt-6, ), emergence = xt ); 2. A model of a neuronal network in to 8 terms of serial time are using for predict the next 2 terms; 3. A model !
of neuronal network in to 6+2(t-1) terms of serial time are using for
predict the next ¡§t¡¨ terms. ƒæ the employment of a new index BPL for the prognosis of sweepings administration consulting of: 1. population (the index of variety of population); 2.¡§the habitat¡¨ of sanitation services; 3. economic development: „« the economic development with £\% / year represents an increase of assimilated sweepings amount emanated from shop keeping (Pce ¡V the economic development percent ); „« the grows with £]% / year of purchase represent an increase of sweepings (Pv ¡V the purchase grows percent) 4. the amount of sweepings collected from population and economics agents; 5. the amount of sweeping from gardens, plaza and streets; 6. the amount of mud from service station, from buildings and knockings. For prognosis of sweepings administration development for a certain region and for a certain period of time, are used the scripts. For certain period are constituted the purposes and aims for short , medium and long time. Each script must have th!
e same base which includes the historical evolution of generation system of sweepings for a period between 5 and 7 years. Inside of scripts are constituted the alternatives. Each alternative describe an integrated system of management of sweepings which includes the available and practical operating method of recycle, treatment and elimination of sweepings. The main criterions of selection for the best script have to accomplish the principles of permanent development: - to have minimal negative effects about environment; - to be permissible in socially; - to be doable in economically.
Keywords: neural network, sweeping administration, prognosis, economic development, serial time
EXTENSION of the file: .pdf
Special (Invited) Session: The implementation of clean production
Organizer of the Session: 599-333
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